Page 1
General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.
Users may download and print one copy of any publication from the public portal for the purpose of private study or research.
You may not further distribute the material or use it for any profit-making activity or commercial gain
You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from orbit.dtu.dk on: Dec 09, 2020
Phenomena-based Process Synthesis-Intensification
Garg, Nipun
Publication date:2019
Document VersionPublisher's PDF, also known as Version of record
Link back to DTU Orbit
Citation (APA):Garg, N. (2019). Phenomena-based Process Synthesis-Intensification. Technical University of Denmark.
Page 2
DTU Chemical EngineeringDepartment of Chemical and Biochemical Engineering
Phenomena-based Process Synthesis-Intensification Nipun Garg
Page 3
Phenomena-based
Process Synthesis-Intensification
PhD Thesis
Nipun Garg
October 2019
KT Consortium
Department of Chemical & Biochemical Engineering
Technical University of Denmark
Page 5
i
Preface
This dissertation is submitted as partial fulfillment of the requirements for the degree of Doctor
of Philosophy (PhD) in chemical engineering at the Technical University of Denmark (DTU).
The PhD project has been carried out at the KT Consortium research group of the Department
of Chemical and Biochemical Engineering, from October 15, 2016 to October 14, 2019, under the
supervision of Professor John M. Woodley (from Process and Systems Engineering (PROSYS))
and Professor Georgios M. Kontogeorgis (from Center for Energy Resources Engineering (CERE))
at the Department of Chemical and Biochemical Engineering, Technical University of Denmark.
The project has been funded by scholarship from KT Consortium and Chemical and Biochemical
Engineering Department at Technical University of Denmark.
Nipun Garg
Kgs. Lyngby, October 2019
Page 7
iii
Acknowledgements
This dissertation is a result of exponential learning, experiences and several challenges that I
could not have succeeded in dealing alone. So, I would like to thank my supervisors, colleagues,
friends in Denmark and India and my family to make these years a fulfilling adventure.
First and foremost, I would like to take this opportunity to express my sincere gratitude and also
appreciation to my supervisors Prof. John M. Woodley and Prof. Georgios M. Kontogeorgis for
their invaluable guidance, their insights, their support and encouragement during tough periods
and their teaching during these three eventful years. Their feedback, constructive criticism,
motivation, belief and confidence in me has surely transformed me into a better researcher and
a person with improved technical and interpersonal skills. I will always be grateful to them for
their valuable time over these years.
I would like to genuinely thank my former supervisor, Prof. Rafiqul Gani for not only providing
this opportunity to work on a challenging and innovative project, but also for sharing his own
viewpoint and perspectives about Process Systems Engineering (PSE). His teachings and the
guidance have been very inspiring and instrumental in shaping and broaden my thought process.
I would also like to express my gratitude to Anjan, who has always been available for technical
conversations and moral support. Thank you Anjan for long invigorating discussions. I am also
thankful to Eva, who has always been there to help me with a smiling face. Thank you for being
a motherly figure to me in Denmark. I was also fortunate to be in a positive working environment,
surrounded by colleagues from KT Consortium, Spardha, Yuqiu, Olivia and Xinyan. So, a thanks
to them for exchange of ideas and all fruitful discussions over these three years.
My friends in Denmark have played a huge role during these three years. For that, I would like
to specially thank Shivangi, Ishan, Alay, Harshit, Fazeel, Mayur, Yash, Swati and Chitta for their
belief and trust. Without their support, it won’t have been possible to complete this journey.
Above all, I would like to thank my parents, my brother Shagun, as well as my friends Anish
(specially), Balwinder, Sukhchain, Gurpreet, Bhupinder, Sonam, Seema and Priyanka in India for
their continuous support and understanding over the past three years.
Thank-you once again to all!
Nipun Garg
Kgs. Lyngby, October 2019
Page 9
v
Abstract
Process synthesis methods generally deals with identification of reactions required to produce
desired products, identification of downstream processes to obtain desired product purity and
decision making in terms of their sequencing. These process synthesis problems are generally
open ended and combinatorial that can generate number of solutions using different approaches.
However, the solution entirely depends on the considered search space and thus are limited to
existing unit-operations hindering the generation of innovative solutions that could significantly
improve the process performance and efficiency by effectively using the maximum driving force
available for a task. Thus, one of the practical ways to generate more efficient, economic and
sustainable process alternatives, counter ongoing challenges and future problems is to develop
approaches and methods that are generic in nature and can be applied over a wide search space
to determine innovative and hybrid/intensified solutions. Process Intensification (PI) is one of
the approach that has enormous potential to achieve this objective. A recent trend in terms of
holistic PI approaches is the use of bottom-up approach that diverts from traditional unit-
operation based approaches within process synthesis and process intensification. These bottom-
up approaches are based on the physicochemical phenomena/functions/building blocks at the
lower level of aggregation increasing the search space and thus generating novel and innovative
solutions at higher level i.e. unit-operation level. The research work done in this project is based
on phenomena-based bottom-up approach.
The main objective of this work is the development and application of systematic phenomena-
based synthesis-intensification framework for direct and indirect synthesis of novel, innovative
and intensified solutions without pre-postulation of possible unit-operations. The fundamental
pillars of this framework are definition and use of the phenomena building blocks (PBBs) that
includes all possible phases (spanning vapor, liquid and solid), identification of phenomena using
thermodynamic insights that are combined using the combination rules and generation of a
phenomena-based superstructure to systematically identify novel, innovative and intensified
flowsheet alternatives. The generated flowsheet options are ranked based on Enthalpy Index (EI)
to identify potential alternatives for detailed analysis (economics, sustainability and life cycle
analysis). One of the novel features of this framework is that it is capable of not only generating
more economic and sustainable novel intensified solutions for an existing process flowsheet
(indirect synthesis or retrofit) but also allows the simultaneous direct synthesis-intensification
by generating phenomena-based superstructure using the phenomena-based approach without
any prior information about the process. Alongside, new phenomena and their classes are
introduced over entire search space, systematic algorithms based on thermodynamic insights are
developed to identify the desirable phenomena and combine them in order to generate novel
Page 10
vi
and intensified solutions. The developed framework is multiscale as it operates at phenomena,
task and unit-operation scale.
The framework developed in this work along with associated algorithms, knowledge bases and
tools are tested with three case studies: production of Dimethyl Ether (DME) from methanol,
production of benzene by Hydrodealkylation (HDA) of toluene and biological production of
succinic acid. The framework is tested for both direct and indirect synthesis-intensification
application. In each of the case study, several novel, innovative and intensified alternatives are
systematically generated using this approach.
Page 11
vii
Resumé På Dansk
Metoder til processyntese beskæftiger sig generelt med identificering af de nødvendige
reaktioner til at producere det ønskede produkt, identificering af oprensningsprocesser for at
opnå de ønskede produkt renhed samt beslutningen om hvorledes deres rækkefølge skal være.
Processyntese problemstillingen er som regel åbne og kan kombineres til at generere adskillige
løsninger ved brug af forskellige fremgangsmåder. Disse løsninger er helt afhængige af det
søgefelt der er taget i betragtning og er dermed begrænset til på forhånd eksisterende
enhedsoperationer, hvilket forhindrer genereringen af innovative løsninger der kunne forbedre
processernes ydeevne ved effektivt brug af den maximale drive kraft tilgængelig for den givende
opgave der skal udføres. Derfor, er en af de mest praktiske måder til at generere mere effektive,
billigere og mere bæredygtige procesalternativer der er med til at bekæmpe nuværende og
fremtidige udfordringer at udvikle fremgangsmåder og metoder der er generiske i deres natur og
som kan bruges i et bredt søgefelt til at identificere innovative og hybride løsninger (proces
intensivering). Proces Intensivering (PI) er en fremgangsmåde der har et enormt potentiale til at
opnå dette mål. De seneste tendenser i forbindelse med holistiske PI fremgangsmåder er brugen
af ”bottom-up” metode der adskiller sig fra den traditionelle enhedsoperation, baserede
fremgangsmåder indenfor processyntese og proces intensivering. Disse bottom-up-
fremgangsmåder er baseret på de fysisk-kemiske fænomener/funktioner/ byggeblokke på det
lavere aggregeringsniveau, hvilket øger søgerummet og genererer således nye og innovative
løsninger på højere niveau, dvs. enhedsdriftsniveau. Forskningsarbejdet udført i dette projekt er
baseret på fænomenbaseret bottom-up-tilgang.
Hovedformålet med dette arbejde er at udvikle og anvende en systematik fænomen baseret
syntese-intensivering ramme til at syntetisere direkte og indirekte nye, innovative og intensiveret
procesløsninger uden nogle på forhånd postulater angående mulige enhedsoperationer.
Fundamentet for denne ramme er at definere og anvende fænomen byggeblokke (phenomena
building blocks (PBBs)) der inkludere all faser (gasfase, væskefase og fastfase), at identificere de
nødvendige fænomener ved brug af termodynamisk indsigt der kombineres ved brug af
kombinationsregler samt at generere fænomenbaserede superstruktur til systematisk
identifikation af nye, innovative og intensiveret processkema alternativer. De genereret mulige
processkema er rangeret i forhold til deres Entalpi Indeks (EI) til at identificere potentielle
alternativer til en mere detaljeret analyse (økonomisk, bæredygtighed og livscyklus analyse). En
af nøglefunktionerne for denne ramme er at den er i stand til ikke kun at generere mere
økonomiske og bæredygtige nye intensiveret løsninger for et eksisterende processkema
(indirekte syntese eller retrofit) men også muliggøre samtidigt direkte syntese-intensivering ved
at generer fænomen baserede superstruktur ved brug af det fænomen baserede fremgangsmåde
Page 12
viii
uden nogle på forhånd kendskab til processen. Yderligere, nye fænomener og deres klassifikation
er introduceret over hele søgefeltet, systematiske algoritmer baseret på termodynamiks indsigt
er udviklet til at identificere de ønskede fænomener og kombinere dem til at generer ny
intensiveret løsninger. Den udviklet ramme er multiskala siden den opererer på fænomen,
opgave og enehedes operation skalaer.
Den udviklede ramme i dette arbejde sammen med de tilhørende algoritmer, viden og værktøjer
er testet på tre casestudier: produktionen af Dimethyl Ether (DME) fra metanol, produktionen
af benzen ved Hydrodealkylering (HDA) af toluen samt biologisk produktion af ravsyre. Rammen
er testet for direkte og indirekte syntese-intensivering applikationer. I hvert tilfælde var der flere
systematiske nye, innovative og intensiverede alternativer ved brug af denne fremgangsmåde.
Tak til Adem for dansk oversættelse af abstraktet.
Page 13
ix
Contents
Preface ................................................................................................................................................................... i
Acknowledgements ........................................................................................................................................ iii
Abstract ................................................................................................................................................................ v
Resumé På Dansk ........................................................................................................................................... vii
Contents ............................................................................................................................................................... ix
Abbreviations and Nomenclature ........................................................................................................... xiii
PART - I
Chapter 1: Introduction ................................................................................................................................. 3
1.1. Process synthesis .................................................................................................................................. 4
1.2. State of the art: Process intensification ........................................................................................ 5
1.2.1. Classification of process intensification ............................................................................................... 7
1.2.2. Bottom-up approaches ............................................................................................................................... 9
1.3. Chapter summary .............................................................................................................................. 12
Chapter 2: Thesis Scope .............................................................................................................................. 13
2.1. Background and motivation .......................................................................................................... 14
2.2. Objectives of the thesis .................................................................................................................... 15
2.3. Thesis structure ................................................................................................................................. 16
2.4. Dissemination of the PhD project results ................................................................................. 16
2.5. Chapter summary .............................................................................................................................. 19
PART - II
Chapter 3: PBS-Intensification: Definitions and Concepts ............................................................. 23
3.1. Definitions ............................................................................................................................................ 24
3.1.1. General definitions .................................................................................................................................... 24
3.1.2. Phenomena related definitions ............................................................................................................ 24
3.2. Concept behind phenomena-based synthesis ......................................................................... 25
3.2.1. Phenomena building blocks (PBBs) ................................................................................................... 25
3.2.2. Simultaneous phenomenon building block (SPB) ........................................................................ 27
3.2.3. Basic structure of SPBs ............................................................................................................................ 28
Page 14
x
3.2.4. Phenomena-based synthesis ................................................................................................................. 29
3.3. Chapter summary .............................................................................................................................. 30
Chapter 4: PBS-Intensification: Methodology and Framework .................................................... 31
4.1. Overview of methodology ............................................................................................................... 32
4.2. Systematic framework ..................................................................................................................... 33
4.2.1. Stage I: Synthesis analysis (step 1-2) ................................................................................................. 33
4.2.2. Stage II: Base case analysis (step 3-4) ............................................................................................... 38
4.2.3. Stage III: Generation of feasible flowsheet alternatives (step 5-11) .................................... 41
4.2.4. Stage IV: Ranking, analysis and comparison (step 12-13) ........................................................ 48
4.3. Chapter summary .............................................................................................................................. 50
Chapter 5: PBS-Intensification: Algorithms, Knowledge bases and Supporting tools ......... 51
5.1. Overview ............................................................................................................................................... 52
5.2. Algorithms ............................................................................................................................................ 53
5.2.1. Algorithms: Stage I ..................................................................................................................................... 53
5.2.2. Algorithms: Stage II ................................................................................................................................... 54
5.2.3. Algorithms: Stage III ................................................................................................................................. 58
5.2.4. Algorithm: Stage IV .................................................................................................................................... 72
5.3. Knowledge bases ............................................................................................................................... 73
5.4. Supporting tools ................................................................................................................................. 74
5.5. Chapter summary .............................................................................................................................. 75
PART - III
Chapter 6: Case Studies ............................................................................................................................... 79
6.1. Case study 1: Production of Dimethyl Ether (DME) .............................................................. 80
6.1.1. Framework application ........................................................................................................................... 80
6.1.2. Discussion ..................................................................................................................................................... 99
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene ...........................................................100
6.2.1. Framework application ......................................................................................................................... 100
6.2.2. Discussion ................................................................................................................................................... 119
6.3. Case study 3: Production of Bio-Succinic Acid ......................................................................121
6.3.1. Synthesis and design using superstructure based optimization .......................................... 121
6.3.2. Application of extended phenomena based synthesis method ............................................. 132
6.3.3. Framework application ......................................................................................................................... 135
Page 15
xi
6.3.4. Discussion ................................................................................................................................................... 153
6.4. Chapter summary ............................................................................................................................154
PART - IV
Chapter 7: Conclusions .............................................................................................................................. 159
7.1. Achievements ....................................................................................................................................160
7.2. Conclusions ........................................................................................................................................161
Chapter 8: Future Perspectives .............................................................................................................. 163
8.1. Open challenges and future work ..............................................................................................164
References ...................................................................................................................................................... 165
Appendix A ..................................................................................................................................................... 179
Appendix B ..................................................................................................................................................... 180
Appendix C ...................................................................................................................................................... 181
Appendix D ..................................................................................................................................................... 192
Appendix E ...................................................................................................................................................... 194
Appendix F ...................................................................................................................................................... 197
Appendix G ..................................................................................................................................................... 218
Page 17
xiii
Abbreviations and Nomenclature
Abbreviations
A, B, C, D, Component identities
A1, A2, A3, Algorithm
ATP Aquatic Toxicity Potential
C Cooling
CAMD Computer Aided Molecular Design
CRZ Crystallizer
D Dividing
DME Dimethyl Ether
DPVSU Distillation-Pervaporation in a Single Unit
DVPSU Distillation-Vapor Permeation in a Single Unit
EI Enthalpy Index eq. Equivalent
ES Energy Supply
ES(D) Energy Supply (Direct)
ESA Energy Separating Agent
EWC Energy and Waste Cost
GMF Generalized Modular representation Framework
GWP Global Warming Potential
H Heating
HDA Hydrodealkylation
HEX Heat exchanger
HTC Human Toxicity Carcinogenic
HTPE Human Toxicity Potential by Exhalation
HTPI Human Toxicity Potential by Ingestion
ICAS Integrated Computer Aided System
KB Knowledge Base
L Liquid
LCA Life Cycle Analysis
LD Lethal Dose
L-L Liquid-Liquid
LLE Liquid-Liquid Equilibria
LS Liquid-Solid
M Mixing
M$ Million USD
MeOH Methanol
Page 18
xiv
MINLP Mixed Integer Non-Linear Programming
MLL Membrane Liquid-Liquid
MoT Modelling template
MSA Mass Separating Agent
MVA Material Value Added
MVL Membrane Vapor-Liquid
MVV Membrane Vapor-Vapor
NBP Number of binary pairs
NC Number of Components
NDV Number of Discrete Variables
NEQ Number of Equations
NF Number of Feeds
NP Number of Product
nPBBMAX Maximum number of PBB
NS Number of processing Steps
NS Number of Streams
nSPBMAX Maximum number of SPB
NV Number of Variables
OP Open Path
OPEX Operating expenditures
PBB Phenomena Building Block
PBS Phenomena-based Synthesis
PC Phase Contact
PCOP Photochemical Oxidation Potential
PI Process Intensification
ProCAPRS Process Computer Aided Reaction Path Synthesis
PS Phase Separation
PSE Process Systems Engineering
PSIN Processing Step Interval Network
PT Phase Transition
PV Pervaporation
R Reaction
RM Raw Material
S Solid
SA Separating Agent
SLE Solid-Liquid Equilibria
SPB Simultaneous Phenomena Building block
SS Solid-Solid
TVA Total Value Added
Page 19
xv
UOM Units of Measurement
V Vapor
VL Vapor-Liquid
VLE Vapor-Liquid Equilibria
VP Vapor permeation
VS Vapor-Solid
VV Vapor-Vapor
Y Year
Y/N Yes/No
Nomenclature
$ U.S. Dollar
Avw vander Waals area
CC Cost of chemicals
CRAW Raw material cost
CU Cost of utilities
d Kinetic diameter
dm Dipole moment
Gf Ideal Gas Gibbs Energy of Formation
h Hour
Hcomb Standard Net Heat of Combustion
Hf Heat of Formation
Hfus Heat of Fusion
Hvap Heat of vaporization
i, j components
k Number of PBB
K Kelvin
kg Kilo gram
Kow Octanol water partition coeff
kt Kilo ton
m2 Square meter
Mv Molar volume
Mw Molecular weight
NM Number of inlet streams
NST Number of separation tasks
PA Property of a component
PB Property of a component
Pc Critical pressure
Ptp Triple point pressure
Page 20
xvi
Pvap Vapor pressure
R Reaction
rg Radius of gyration
Rij Binary ratio
SIG Ideal Gas Absolute Entropy
SPROD Product sales
Tazeotrope Azeotrope temperature
Tb Normal Boiling point
Tc Critical temperature
Teut Eutectic temperature
Tm Melting Point
TST Thermal stability temperature
TTD Thermal degradation temperature
Ttp Triple point temp
Vc Critical volume
Vvw vander Waals volume
Zc Critical compressibility factor
α Diffusivity
γ Surface tension
γr,s Stoichiometric coefficient
δ Solubility parameter
ΔHrxn Heat of reaction
ΔH Enthalpy change
δi,j Split fraction
Δvp Stoichiometric coefficient of product
Δvr Stoichiometric coefficient of reactant
ε Separation factor
η Reaction conversion
μ Molar flowrate
σ Molecular diameter
ω Acentric factor
Page 21
1
PART - I
First part of the thesis consists of two chapters. The first chapter
gives brief introduction about process synthesis and the current
need for innovation. Then, the current state of the art for process
intensification (PI) is presented. This includes, the classification
of PI in different categories performed at different scales, level
and within different domains. A summary of different limitations
identified for primary tasks that can be overcome using process
intensification approaches are also mentioned. Further, a novel
approach for PI i.e. bottom-up approach is discussed primarily as
current work is based on it. An overview of different bottom-up
approaches is presented along with their challenges. Bottom-up
approaches generate innovative intensified solutions using non-
traditional approach that departs from unit-operation. In chapter
2, the objectives and the scope of the thesis are defined based on
the background and motivation behind this work. The thesis
structure is also presented which is divided into 4 parts and 8
chapters. A brief overview of the PhD project results that are
disseminated through various journal articles, international peer
reviewed conference publications, oral and poster presentations
is also presented in chapter 2.
Page 23
1.1. Process synthesis
3
Chapter 1
Introduction
Chapter outline:
1.1. Process synthesis
1.2. State of the art: Process intensification
1.2.1. Classification of process intensification
1.2.2. Bottom-up approaches
1.3. Chapter summary
These journal articles are partially based on this chapter:
Garg, N., Kontogeorgis, G.M., Gani, R. and Woodley, J.M., 2019, “A process synthesis-
intensification method for generation of novel and intensified solutions”, in preparation.
Garg, N., Woodley, J.M., Gani, R. and Kontogeorgis, G.M., 2019, “Sustainable solutions
by integrating process synthesis-intensification”, Computers and Chemical Engineering,
126, 499-519.
In this chapter, first, an overview of the need for novel and innovative solutions is
explained. Then, the process synthesis and process intensification are introduced
and described. An overview of the state of the art for process intensification is
discussed from the Process Systems Engineering (PSE) point of view. Different
approaches to perform PI are also discussed. A particular emphasis has been given
on bottom-up approaches as research in this thesis is based on phenomena-based
synthesis which is also a bottom-up approach. Bottom-up approaches are ones
that depart from the conventional unit-operation based approach and thus
operate at lower level of aggregation. Here, an overview of several other bottom-
up approaches developed over the years is also presented.
Page 24
Introduction
4
The journey to attain sustainable production in chemical and related industries is still in its early
stages and there is a continuously rising expectation for improvement and innovation in the
coming years (Välimäki, 2018). These chemical and biochemical processes produce products that
are essential in daily life and become more and more important in meeting the requirements of
today’s modern world. Simultaneously, they are also exerting negative impacts on the ecosystem.
These impacts are generated because of many factors like excessive and inefficient use of natural
resources, waste discharge into the environment, ecological effect of the products, inefficient
methods of production to name a few. These industrial processes span the chemical, petroleum,
pharmaceutical, food, textile, electronic and bio-industry. For all these industries, along with
economic benefits, maintaining sustainability, i.e., conserving the resources, preventing waste
generation and increasing productivity have also become top priority. Thus, there is an increased
interest in generation of innovative processes that are not only economically beneficial but are
sustainable as well.
1.1. Process synthesis
The aim of process synthesis is to identify an optimal processing route to convert a set of raw
materials into the desired products subject to any predefined performance criteria or design
constraints (Gani and Babi, 2014). The performance criteria can be defined in many different
ways for example, product (s) purity, reduced energy consumption, and better environmental,
life cycle or sustainability factors. An overview of process synthesis problem is given in Figure 1.1.
Figure 1.1: Overview of process synthesis problem
Several process synthesis approaches are developed in past many years that are primarily
categorized as heuristics or knowledge based methods (Siirola et al., 1971; Stephanopoulos &
Westerberg, 1976; Douglas, 1985; Jaksland et al., 1995; Siirola, 1996; Jaksland & Gani, 1996; Seader
& Westerberg, 1997; Sempuga et al., 2010; Fox et al., 2013), mathematical optimization based
methods (Floudas et al., 1986; Floudas, 1987; Yee and Grossmann, 1990; Kokossis, 1990; Kokossis
& Floudas, 1994; Papalexandri & Pistikopoulos, 1996; Zondervan et al., 2011; Quaglia et al., 2012)
and hybrid methods (Lu & Motard, 1985; Steffens et al., 2000; Hostrup et al., 2001; Rigopoulos
and Linke, 2002; Tula et al., 2014).
Page 25
1.2. State of the art: Process intensification
5
However, process synthesis is generally limited to existing unit operations and thus, novel and
intensified/hybrid solutions are not generated or included (Bednik et al., 2004; Li et al., 2011;
Babi et al., 2015). Thus, an extension of search space in process synthesis is required to generate
innovative solutions meeting the desired objectives. Therefore, traditional concepts of process
synthesis need to be expanded to generate novel and innovative solutions. These concepts can
be expanded in a way that considered problem incorporates additional constraints for desired
performance or targets the maximum driving force behind every task.
One of the ways to achieve this objective is by integrating process synthesis and intensification.
By performing process synthesis-intensification, the current search space of process synthesis
can be increased to generate new, novel and innovative solutions.
1.2. State of the art: Process intensification
Process Intensification (PI) aims to significantly improve the process performance and bring
improvements both in terms of sustainability and economics. It has emerged to be an important
tool providing development opportunities and solutions for the challenges generating more
efficient and sustainable processes. Ozokewlu, 2014 has presented a list of an interdisciplinary
application of PI to different industrial sectors. A brief overview of the applications but not only
limited to is shown in Figure 1.2.
Figure 1.2: An overview of process intensification application to industrial sectors
The term Process intensification first attracted serious attention in the early 1970’s but has one
of the earliest references in a paper published by Wightman et al. (1925). Back then the term
Process Intensification
Chemical manufacturing
✓Integrated process steps
✓Modular processes
Petroleum refining
✓Gas to liquid conversion
✓Wastewater treatment
Oil and gas extraction
✓Hydro-fracturing
✓Gas processing and recovery
Biochemical production
✓Integrated fermentation
✓Choice of host
✓Engineered strains
Power generation
✓Gas separation
✓Carbon capture
Waste and recycling
✓Membrane systems
✓Electronics recycling
Page 26
Introduction
6
process intensification was mainly described as process improvement (Reay et al., 2008). Since
then, in past many decades, understanding of PI has changed and thus different definitions have
been proposed by different researchers. As per the Rapid Advancement in Process Intensification
Deployment (RAPID) manufacturing Institute, PI is considered as a transition from pure unit
operation thinking to a more integrative approach (https://www.aiche.org/rapid). An extensive
and comprehensive review of different definitions, technologies, and tools to perform PI and
increasing interest over time is given by Tian et al. (2018). Tian et al. (2018) mentions that, “PI is
often considered as a toolbox having certain examples for process improvement rather than a
powerful, systematic and strategic approach for innovation”. Thus, the full potential of PI is yet
to be explored in generating systematic, more sustainable, innovative and efficient solutions.
One of the best-known, commercial applications of PI is the methyl acetate production process
using reactive distillation by the Eastman chemical company (Agreda et al., 1990). Here, five
processing steps are integrated to achieve 80% reduction in energy and a large reduction in
capital cost. Other successful developments of PI are membrane reactor (Gallucci et al., 2008),
static mixers (Kim et al., 2017), membrane distillation (Calabro et al., 1994), heat exchanger
reactor (Anxionnaz et al., 2008), reverse flow reactor (Smith and Mackley, 2006) etc. Also, in
bio-processes, PI principles are applied, for example, in fermentation operations. Opportunities
like application of cell retention and insitu removal of products can significantly improve
fermentation processes. The main challenge here for PI is to have reasonably accurate estimates
to find the optimal balance between transport, mixing and kinetics - improving the performance
of fermentation processes (Noorman et al., 2018). Besides, there are PI technologies that are
developed at a lab scale but have not yet found application at industrial level (for example
technologies using external energy sources like microwave, ultrasound, centrifugal and electric
fields). Some of the challenges that restrict the deployment of developed intensified technologies
include the risk of failure, scale-up unknowns, unreliability of equipment performance, and
uncertain safety, health, and environmental impacts (Quadrennial Technology Review, 2015).
Table 1.1: Summary of limitations addressed in reaction and separation tasks
Reaction Task Separation task
Energy consumption Energy consumption
Low selectivity (reaction) Limited mass transfer
Unfavorable equilibrium
or low yield
Difficult separation (low
driving force)
Limited heat transfer Limiting equilibria/azeotropes
High contact time High capital costs/large
volume/no. of units High capital cost, large
volume, no. of units
Page 27
1.2. State of the art: Process intensification
7
Lutze, (2011) explained that, the main driver behind PI is to overcome limitations behind driving
the task in the process identified as process hotspots. In a detailed literature survey performed
by Lutze, (2011), the main limitations that have been overcome by using PI in reaction and
separation task are shown in Table 1.1.
PI can be performed in many ways i.e. by integrating unit operations (for example, a sequence of
the reactor and distillation columns), integrating tasks (for example, an integrated reaction and
separation in the membrane reactor or reactive distillation column) or by integration and/or
enhancement of phenomena/physiochemical functions affecting the driving force of a task or set
of tasks (Lutze et al., 2013; Babi et al., 2015; Garg et al., 2019).
Figure 1.3: Different ways to perform PI (R and S denotes reaction and separation)
As shown in Figure 1.3a and 1.3b, there are not many alternatives when PI is performed at unit
operation or task levels. However, as shown in Figure 1.3c, the same task (left-hand side of Fig
1.3c) can lead to new intensified equipment such as reactive distillation, membrane-based
reactor-separator (right-hand side of Fig 1.3c) through different combinations of phenomena
(middle of Fig 1.3c). Note that in Fig 1.3c, only a few combinations of phenomena are highlighted.
1.2.1. Classification of process intensification
Process intensification can be classified into various approaches as shown in Table 1.2. These are
explained as follows:
a) Integration of Unit Operations b) Integration of Tasks
R-S-Task
c) Integration and/or enhancement of phenomena
M(VL)=2phM
M(VL)=2phM=R=PC(VL)=PT(PVL)=PS(VL)
M(V)=C
R-Task S-Task
M=C=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=R=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=H=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PS(LL)
M=C=PC(LS)=PT(LS)=PS(LS)
S-Task
M=PC(MLL)=PS(LL)
M=ES(C)
M=PT(LS)=PS(LS)
M=ES(C)=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=R=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=R=ES(C)
M=PC(MVL)=PS(VL)
Page 28
Introduction
8
Table 1.2: Overview of process intensification approaches
Process
Intensification
Categories Heuristic based methods, Mathematical programming
based methods, Hybrid methods
Levels Process level, Unit-operation level (section of process)
Scales Phenomena scale, Task scale, Unit-operation scale
Domains Process structure domain, Energy domain, Synergy
domain, Time domain
Categories and levels of PI
Process intensification approaches can be broadly classified into different categories performing
at different levels: heuristic, mathematical programming, and hybrid approaches.
o Heuristic based PI approaches: Heuristic approaches are based on information or rules
which are built over time from experiences, different problem insights, engineering data,
and thumb rules. Several heuristics-based process intensification methods are developed
where research from Bessling et al. (1997) and Kiss et al. (2007) focuses on intensification
of a particular section of a process while work from Siirola, (1996) and Portha et al. (2014)
intensify the entire process.
o Mathematical programming-based PI approaches: The mathematical programming
approaches determine the optimal solution through superstructure based optimization
techniques. Examples of the mathematical programming approaches are Caballero and
Grossmann, (2004), Ramapriya et al. (2014), Chen and Grossmann, (2017) where section
of a process is intensified, while, methods from Papalexandri and Pistikopoulos, (1996),
da Cruz et al. (2017), Li et al. (2017) and Demirel et al. (2017) perform intensification of
the entire process or a part of the process at different scales.
o Hybrid approaches for PI: Hybrid approaches aim at combining the advantages of both
heuristic and mathematical programming approaches. These generally concentrate on
narrowing down the search space to reduce the size of the problem by removing
redundant alternatives. Examples of hybrid approaches are Freund and Sundmacher,
(2008), Peschel et al. (2012) and Seifert et al. (2012) intensifying a section of process
while Lutze et al. (2013), Babi et al. (2015), Tula et al. (2017) and Garg et al. (2019) have
reported multiscale methods to intensify the whole or a part of process.
All these categories have certain advantages and disadvantages. Heuristic based approaches are
simple, fast and generally give suggestions for improvement/optimization of an existing process
or development of a new process similar to the existing ones. However, these approaches lack
generality and also requires an extensive knowledge base for reliable results. Mathematical
programming based approaches are advantageous in a way that the optimization of both process
and conditions are done simultaneously, thus all the interactions are considered while solving
Page 29
1.2. State of the art: Process intensification
9
the problem. However, the solution relies highly on the superstructure of alternatives
considered. Thus, in order to have the most optimal solution, it has to be present in the original
search space. Hybrid approaches have simple structure (comes from heuristics) and narrows
down the search space by eliminating the redundant solutions using the thermodynamic
insights. However, the screening may remove non-intuitive optimal solutions.
Scales and domains of PI
PI can be achieved at various scales across different domains. According to Babi et al. (2015), PI
can be performed at different scales, i.e., unit operation, task and phenomena scale. At unit
operation scale, individual unit operations that constitute the process are considered for
intensification. Further, at the task scale, the functions performed by a specific unit-operation
are considered. A task can be defined as a purpose that it fulfills in the process such as reaction,
separation, mixing or energy supply. Examples of PI performed at unit operation and task scales
are dividing wall column, membrane reactor and reactive distillation (Inoue et al., 2007; Asprion
and Kaibel, 2010; Halvorsen and Skogestad, 2011; Holtbruegge et al., 2015; Demirel et al., 2017).
At phenomena scale, different phenomena affecting the driving force to perform a task are
identified and further combined to generate innovative and intensified alternatives. Some of the
examples of PI methodologies that operates at the phenomena scale are Papalexandri and
Pistikopoulos, (1996), Arizmendi-Sánchez and Sharratt, (2008), Rong et al. (2008), Lutze et al.
(2013), Babi et al. (2015), Garg et al. (2019). According to Van Gerven and Stankiewicz, (2009),
these improvements or enhancements can be achieved across four different domains that are
process structure, energy, synergy and time. Time domain involves improvement of the kinetics,
reduction of time, i.e., maximization of the speed and effectiveness of the events at different
scales. Space domains consider maximization of homogeneity, for example, creation of identical
conditions for each molecule within the considered system. Energy (or thermodynamics) domain
includes relaxation of transport limitations thus maximizing the driving forces and various
transfer areas. Synergy domain aims to maximize the integration of different tasks, for example,
reaction combined with heat exchanger or alternative energy source like microwave to improve
overall performance.
1.2.2. Bottom-up approaches
The latest trends in the holistic and systematic PI is use of the bottom-up approaches that are
departing from the conventional unit-operation based approach and instead using processing
task, physicochemical phenomena and functions to increase the search space and generate
innovative solutions. These approaches focus on generating intensified solutions starting from a
lower scale of aggregation and gradually moving upwards to the unit-operation scale. Bottom-
up approaches are also advantageous in comparison to traditional process synthesis and design
methods as unit operation-based representation may hinder the exploration and discovery of
out-of-the-box solutions and design alternatives.
Page 30
Introduction
10
Over the years, several bottom-up approaches have been proposed (Figure 1.4). Papalexandri and
Pistikopoulos, (1996) introduced phenomena scale for the first time and proposed a “phenomena
based generalized modular representation framework (GMF)” that uses fundamental mass/heat
transfer principles and optimizes them based on Gibbs free energy. The framework also involves
the generation of superstructure which is optimized with mixed integer non-linear programming
(MINLP) formulation to find the process alternatives.
Figure 1.4: An indicative timeline tree of bottom-up approaches
Rong et al. (2004, 2008) introduced a 3-stage phenomena-based approach for PI using physical
and chemical insights to overcome the thermodynamic limitations. In the first stage, the process
bottlenecks are identified. In the second stage, phenomena are identified on basis of bottlenecks
and finally, in stage 3 alternatives are generated via replacing actual equipment with better suited
equipment. Arizmendi-Sánchez and Sharratt, (2008) developed a framework for phenomena-
Papalexandri
and
Pistikopoulos
1996
Rong et al.
2004, 2008
2008
Arizmendi-Sánchez
and Sharratt
2008Freund and
Sundmacher
2010, 2011
Peschel et al.
2013
Lutze et al.
2015
Babi et al.
2017, 2018Demirel et al.
and Li et al.
2017
Kuhlmann and
Skiborowski;
Kuhlmann et al.
Tian et al.Garg et al.
2018
2019
Page 31
1.2. State of the art: Process intensification
11
based PI using the modularization principles. In this work, the physicochemical phenomena are
arranged to represent the behavioural level consisting of accumulation, generation and transport
of mass and energy bounded by structural phenomena. Modularization criteria are then used to
ensure consistency of qualitative (knowledge based) and quantitative (causal graphs) models.
Freund and Sundmacher, (2008) introduced functional modules (in terms of linear combination
of elementary process functions and flux vectors) to represent equipment independent process
flowsheets. This assisted in identifying potential areas where intensification can be applied.
Peschel et al. (2010, 2011) used this novel description of a chemical process to develop a 3-level
approach generating novel reactor network system. This included the selection of an optimal
reaction route amongst different alternatives followed by mass and energy balance for catalyst
packing and then finally, technical constraints were determined for the equipment.
Demirel et al. (2017) and Li et al. (2017) proposed a 2-D grid representation of abstract building
blocks (ABB) similar to phenomena/functions where a structure of different types of blocks
results in an intensified unit-operation. Overall design problem includes vapor-liquid search
space and is formulated as a single MINLP problem. The work has been extended to perform
simultaneous synthesis, integration and intensification. Tian and Pistikopoulos, (2018) proposed
an integrated approach that enables automated generation of safely operable PI systems from
phenomena level using the GMF developed by Papalexandri and Pistikopoulos, (1996). Here, a
multiperiod GMF representation for vapor-liquid systems is developed to ensure that the design
configurations can be operated under a specified range of uncertain parameters.
Lutze et al. (2013) with inspiration from Papalexandri and Pistikopoulos, (1996)’s phenomena-
based research, proposed an innovative and systematic methodology analogous to CAMD
performing process intensification at phenomena scale. The methodology uses phenomena
building block (PBB) to describe the process and sequentially using predefined rules and
algorithms, combine them to generate simultaneous phenomena building blocks (SPBs) which
are translated to unit operations. The phenomena-based methodology initially proposed by
Lutze et al. (2013) was extended by Babi et al. (2015) adding economic, sustainability and Life
cycle considerations to intensify an existing entire process. Babi et al. (2015) proposed a 3-stage
approach wherein stage 1 and 2, a base case flowsheet is identified and designed in detail to
identify process hotspot and set design targets followed by generation of improved, innovative
and intensified alternative using phenomena based intensification (stage 3). The 3 stages can also
be performed independently, depending on available input information. For example, if a process
flowsheet already exists, stage 2 can be performed directly. The phenomena-based methodology
from Babi et al. (2015) has been further enhanced to generate innovative solutions involving
solid-liquid and liquid-liquid systems in addition to vapor-liquid and membrane systems that
could be intensified previously (Garg et al., 2019). Kuhlmann and Skiborowski, (2017), proposed
a methodology generating intensified flowsheet variants for predefined separation tasks based
Page 32
Introduction
12
on a superstructure of the PBBs that are subsequently translated into specific equipment. The
methodology is further updated for reaction-separation tasks by Kuhlmann et al. (2017). Here,
among these approaches, an existing process flowsheet or a base case is required to perform
process synthesis-intensification at different levels.
1.3. Chapter summary
An overall concept of process synthesis, related approaches and associated methods has been
presented. Process synthesis approaches being generally limited to existing unit-operations
limits the creativity to find novel and intensified solutions. Thus, an opportunity to expand the
current search space provided by PI was discussed. Process intensification is a valuable tool for
the development of more sophisticated and more efficient processes aimed at the sustainable
production in chemical and related industries. One of the many objectives of Process Systems
Engineering (PSE) domain is to generate innovative solutions which is well in harmony with all
or several of the process intensification approaches. Thus, PSE community is making continuous
efforts within PI to address the key issues like: (i) efficient use of process systems methods to
utilize wide search space and develop systematic methods that can generate out of the box
solutions (ii) ensuring operability performance of the generated intensified solutions at an early
design stage (Tian and Pistikopoulos, 2018).
This chapter also provided an overall concept of process intensification with a detailed overview
of bottom-up approaches, different thoughts, associated methods, and applications to achieve
process intensification. There are several approaches developed under PI, out of which the latest
trend is the bottom-up approaches. Bottom-up approaches provide an opportunity to create out
of the box solutions by operating at the lowest level of aggregation and thus moving upwards
towards unit-operation based flowsheets generating intensified solutions and its configurations.
Summarizing, some of the big challenges for Process Systems Engineering (PSE) based process
synthesis-intensification approaches are as follows:
o Systematic identification: How systematically novel and innovative intensified process
pathways can be identified spanning wide search space.
o Systematic synthesis: How systematically novel, innovative and intensified process
alternatives can be generated from the beginning i.e. without needing any base case or
an existing process hotspot information.
o Systematic validation: How systematically generated novel and innovative intensified
solutions can be validated in terms of safety and operability.
Page 33
1.3. Chapter summary
13
Chapter 2
Thesis Scope
Chapter outline:
2.1. Background and motivation
2.2. Objective of the thesis
2.3. Thesis structure
2.4. Dissemination of the PhD project results
2.5. Chapter summary
This chapter firstly, presents the background and motivation behind this project
and also explains the scope of the thesis. The need for a systematic and integrated
approach for process synthesis and process intensification generating novel and
innovative solutions is also described. The objectives of the thesis are explained
on the basis of the literature review presented in chapter 1. Then, the structure of
the thesis is presented that consists of eight chapters across four parts which are
introduction, developed framework (includes concept, framework, algorithms and
knowledge bases), application examples and conclusion. An overview of the PhD
project results disseminated via various journal articles, international conference
publications, oral, and poster presentations is also presented.
Page 34
Thesis Scope
14
2.1. Background and motivation
In order to meet ever-growing demands, chemical and related industries are constantly looking
for solutions that are economical, sustainable, efficient, and are easily applicable and scalable.
The major challenges associated and being faced while achieving these objectives are:
a) How systematically, innovative and sustainable solutions can be achieved?
b) How different solutions can be efficiently and quickly screened and assessed?
c) How the complexities of the industrial processes can be managed?
d) How to achieve guaranteed non-trade off solutions for example from an environmental,
technical and economic perspective?
Thus, in recent years, a major focus in process technology has been on hybrid/intensified and
novel equipments that can dramatically improve the performance of chemical and biochemical
processes. Therefore, tools, techniques, and methodologies that potentially could transform the
basics of process synthesis and design; generating novel, innovative and sustainable solutions are
highly desirable. The key attributes of such methods and tools should be that they are systematic,
flexible in applicability and approach as well as covering a wide range of domains and scales from
molecular to process or from phenomena to unit operation scale (Figure 2.1).
Figure 2.1: Key attributes for methods to generate sustainable solutions
Also, from the literature study, we came to know that, bottom-up approaches are beneficial as
they depart from conventional unit-operation based approaches and thus bears the potential to
Key to Methods for Sustainable Solutions
Systematic
Flexible and
versatile
Multi disciplinary and multi
scale
Quick and efficient
Generate innovative
alternatives
Manage complexity
Page 35
2.2. Objectives of the thesis
15
generate novel solutions that are economic and sustainable. Several methodologies over the years
have been developed under bottom-up approaches that can generate a variety of solutions for
different problems. Most of the mentioned approaches are limited to vapor-liquid systems or
reaction/separation systems or requires an existing process flowsheet to generate or synthesize
intensified solutions and thus spans across existing intensified equipment or its configurations.
There is a need of a framework that can systematically generate novel, innovative and intensified
unit-operation/unit-operation based flowsheets while considering the complete search space of
vapor/liquid/solid systems. Also, the framework is not constrained to the presence of existing
process flowsheet or unit-operations to generate innovative and intensified alternatives i.e. it can
perform direct synthesis-intensification. If required, the framework is flexible and can also
perform retrofit or indirect synthesis-intensification to generate more sustainable and economic
solutions than the existing process. Furthermore, it also considers special energy sources for
example microwave, ultrasound to name a few expanding the current search space.
The research performed in this thesis is based on the hybrid approach for process intensification.
Further, the developed framework is a bottom-up approach operating at phenomena scale and
gradually moving towards unit-operation scale to generate novel and innovative solutions. The
research done by Lutze, (2012) and Babi, (2014) is taken as a starting point for this work, to be
adapted and thus develop a novel and unique framework for a variety of applications.
2.2. Objectives of the thesis
Motivated by the needs and identified gaps, in this PhD project a significant effort has been made
to cover most of the challenges covering systematic identification and synthesis; thus, developing
a systematic framework to generate novel, innovative and intensified solutions.
The main objectives of this PhD thesis are as follows:
➢ Direct and indirect synthesis-intensification: To develop a systematic framework
performing direct and indirect synthesis-intensification for chemical and biochemical
processes generating novel, innovative and intensified flowsheet alternatives.
➢ Systematic generation of the novel and innovative solutions: Development of the
methodology for systematic generation of novel and potentially feasible intensified unit-
operations without any apriori postulation for the same.
➢ Search space spanning vapor/liquid/solid systems: Use of the entire search space
covering phenomena/physicochemical functions across vapor, liquid and solid systems.
➢ Phenomena based superstructure: To generate a phenomena based superstructure
based on physical property and thermodynamic insights constituting the entire search
space of alternatives generated from mathematical combination of compounds.
Page 36
Thesis Scope
16
➢ Special energy sources: Inclusion of the special energy sources to expand phenomena
database generating innovative solutions.
➢ Ranking of generated alternatives: Development of a method capable of evaluating
and ranking the generated alternatives without using rigorous models.
Further, applicability of the developed framework to be tested with case study examples.
2.3. Thesis structure
This PhD thesis is divided into four parts including eight chapters described as follows:
PART I (Chapter 1-2) Part I is introductory, consisting of chapters 1 and 2. Here, in chapter 1, state of the art for process
intensification with bottom-up approaches is presented. Chapter 2 presents the thesis scope
including the background and motivation for this work. Further, the main objectives of this work
are stated along with various dissemination activities performed over the course of three years.
PART II (Chapter 3-5) Part II is the core of this thesis consisting of chapters 3, 4 and 5. Chapter 3 presents the basics
and builds the conceptual understanding about the phenomena-based synthesis-intensification
method. In chapter 4, the methodology and the framework developed is presented while chapter
5 consists of algorithms, knowledge bases and supporting tools required to apply the framework.
PART III (Chapter 6) Part III consists of chapter 6, where 3 application case studies of the developed framework are
presented. The three case studies solved are production of DME (direct synthesis-intensification
application of the framework), hydrodealkylation of toluene to produce benzene (indirect
synthesis-intensification application of the framework), and the production of bio-succinic acid
(indirect synthesis-intensification). The difference between second and third case study is that
in second case study the base case is identified from literature while in third case study the base
case is synthesized using superstructure based mathematical optimization approach.
PART IV (Chapter 7-8) Part IV presents the conclusion and future work of the thesis. Chapter 7 outline achievements
and conclusions of this work while chapter 8 provides future perspectives and directions for
further expansion or improvements.
2.4. Dissemination of the PhD project results
This section contains a list of publications, conference presentations and other contributions
related to this PhD project. The results from this PhD work including different collaborations is
disseminated in the form of research articles in scientific journals and articles published in
Page 37
2.4. Dissemination of the PhD project results
17
international conference proceedings. Furthermore, conference presentations (both oral and
poster) presented in various international conferences during the course of PhD study are also
listed. The research work has also been disseminated during several annual meetings via oral and
poster presentations.
Journal publications
1. Garg, N., Kontogeorgis, G.M., Gani R. and Woodley, J.M., 2019, “A process synthesis-
intensification method for generation of novel and intensified solutions”, in preparation.
2. Chen Y., Garg, N., Kontogeorgis, G.M. and Woodley, J.M., 2019, “Systematic screening of
Ionic liquids for bio-processing”, in preparation.
3. Garg, N., Woodley, J.M., Gani, R. and Kontogeorgis, G.M., 2019, “Sustainable solutions
by integrating process synthesis-intensification”, Computers & Chemical Engineering, 126,
499-519.
4. Tula, A.K., Befort, B., Garg, N., Camarda, K. and Gani, R., 2017, “Sustainable process
design & analysis of hybrid separations”, Computers & Chemical Engineering, 105, 96-104.
Peer reviewed international conference publications
1. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “Sustainable and
Innovative Solutions through an Integrated Systematic Framework”, Computer Aided
Chemical Engineering, 44, 1165-1170.
2. Garg, N., Tula, A.K., Eden, M.R., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018,
“Hybrid Schemes for Intensified Chemical and Biochemical Process Alternatives”,
Chemical Engineering Transactions, 69, 517-522.
3. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “A Multi-stage and
Multi-level Computer Aided Framework for Sustainable Process Intensification”,
Computer Aided Chemical Engineering, 43, 875-880.
Contribution to international peer reviewed conferences
1. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., 2019, “A Phenomena based method for
Process Intensification”, Type: Poster, presented at: FOCAPD-2019 conference, Colorado
Springs, Colorado, USA.
2. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “A Multi-stage and
Multi-level Computer Aided Framework for Sustainable Process Intensification”, Type:
Oral, presented at: ESCAPE-28 conference, Graz, Austria.
3. Garg, N., Tula, A.K., Eden, M.R., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018,
“Hybrid Schemes for Intensified Chemical and Biochemical Process Alternatives”, Type:
Oral, presented at: Distillation and Absorption-2018 conference, Florence, Italy.
Page 38
Thesis Scope
18
4. Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “Sustainable and
Innovative Solutions through an Integrated Systematic Framework”, Type: Oral,
presented at: PSE-2018 conference, San Diego, California, USA.
5. Garg, N., Woodley, J.M. and Gani, R., 2017, “A Method for Chemical and Biochemical
Sustainable Process Synthesis, Design and Intensification”, Type: Oral, presented at:
WCCE10 conference, Barcelona, Spain.
6. Garg, N., Woodley, J.M. and Gani, R., 2017, “A Systematic Method for Chemical and
Biochemical Sustainable Process Synthesis, Design and Intensification”, Type: Oral,
presented at: AIChE-2017 conference, Minneapolis, Minnesota, USA.
7. Gani, R., Babi, D.K., Bertran, M., Frauzem, R. and Garg, N., 2017, “The Sustainable
Synthesis-Design-Intensification of Chemical and Biochemical Processes”, Type: Oral
presented by Gani R., presented at: AIChE-2017 conference, Minneapolis, Minnesota, USA.
8. Andersen, T.G., Johansen, M., Andersen M.G. and Garg, N., 2017, “Systematic Process
Design of a Styrene Production Plant Using a Hierarchical 12 Task Procedure: Waste
Stream Utilization for Improved Sustainability”, Type: Poster presented by Andersen,
T.G., Johansen, M. & Andersen M.G., presented at: AIChE-2017 conference, Minneapolis,
Minnesota, USA.
9. Tula A.K., Garg, N., Woodley, J.M., Gani, R. and Befort B., 2016, “Multi-Scale Computer
Aided Synthesis–Design–Intensification Method for Sustainable Hybrid Solutions”, Type:
Oral, presented at: AIChE-2016 conference, San Francisco, California, USA.
Other contributions
1. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “A generic phenomena-based synthesis
method for process intensification”, Type: Oral, presented at: KT Consortium Annual
Meeting-2019, Helsingør, Denmark.
2. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “Phenomena based synthesis-
intensification: generalized method and case studies”, Type: Poster, presented at: KT
Consortium Annual Meeting-2019, Helsingør, Denmark.
3. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “Sustainable and Innovative Chemical
and Biochemical Solutions through an Integrated Systematic Framework”, Type: Oral,
presented at: KT Consortium Annual Meeting-2018, Rungsted Kyst, Denmark.
4. Garg, N., Kontogeorgis, G.M. and Woodley, J.M., “A multi scale and multi-level computer
aided approach for Process Intensification”, Type: Poster, presented at: KT Consortium
Annual Meeting-2018, Rungsted Kyst, Denmark.
5. Garg, N., Woodley, J.M. and Gani, R., “Conversion of Biomass to value added chemicals”,
Type: Poster, presented at: Pro BioRefine-2016, Auburn, Alabama, USA.
Page 39
2.5. Chapter summary
19
6. Garg, N., Woodley, J.M. and Gani, R., “Systematic Chemical and Biochemical Sustainable
Process Synthesis, Design and Intensification”, Type: Oral, presented at: KT Consortium
Annual Meeting-2017, Helsingør, Denmark.
7. Garg, N., Woodley, J.M. and Gani, R., “Phenomena based Process Intensification”, Type:
Poster, presented at: KT Consortium Annual Meeting-2016, Technical University of
Denmark, Lyngby, Denmark.
2.5. Chapter summary
This chapter provided insights about the thesis scope and objectives set to be achieved during
this project. These objectives are set based on the identified needs and gaps in current PSE based
PI approaches and thus tackles many of the unsolved challenges like synthesis of novel flowsheets
without any apriori postulation, wider search space including all the possible phases, alternative
energy sources to name a few. Further, an overview of the thesis structure was presented followed
by a list of dissemination activities during this PhD project.
Page 41
2.5. Chapter summary
21
PART - II
This part of thesis consists of three chapters. These chapters set
the base to understand the developed framework and how it can
be applied to different case studies generating novel, innovative
and intensified solutions. The first chapter in this part (chapter
3) states the general definitions and explains the fundamental
concepts behind the phenomena-based synthesis. The second
chapter in this part (chapter 4) presents step by step, developed
phenomena-based synthesis (PBS)-intensification framework.
The framework consists of 4 stages and 13 steps that are capable
of performing direct and indirect (or retrofit) phenomena-based
synthesis. Each step of the stage has its workflow and data flow,
where the output of one step is input to the following step; that
are also described in detail in this chapter. Also, there are various
algorithms, knowledge bases and tools, which are included in the
framework. All these associated algorithms, knowledge bases
and supporting tools are explained in the third chapter of this
part (chapter 5). This chapter consists of the 12 algorithms and 4
knowledge bases developed across four stages of the framework.
Finally, the simulation software and analysis tools for evaluation
are also presented.
Page 43
23
Chapter 3 PBS-Intensification: Definitions and Concepts
In this chapter, all the definitions and concepts related to this work are presented.
This chapter sets the foundation to apply the systematic framework for various
applications. The definitions provide necessary information and understanding
about the different terminologies that are used either directly or developed in this
project. The phenomena-based synthesis approach is similar to Computer Aided
Molecular Design (CAMD) and thus, the comparison is also explained. In order to
systematically generate the novel and innovative process flowsheet alternatives,
the basic understanding behind the phenomena concepts are also reviewed.
Additionally, general application of these definitions and concepts is also stated
where phenomena are combined at the lower scale of aggregation that can
perform tasks at the higher scale and are converted to unit-operation performing
required task or a set of tasks.
Chapter outline:
3.1. Definitions
3.1.1. General definitions
3.1.2. Phenomena related definitions
3.2. Concepts
3.2.1. Phenomena building blocks (PBBs)
3.2.2. Simultaneous phenomena building block (SPB)
3.2.3. Basic structure of SPBs
3.2.4. Phenomena based synthesis
3.3. Chapter summary
These journal articles are partially based on this chapter:
Garg, N., Kontogeorgis, G.M., Gani, R. and Woodley, J.M., 2019, “A process synthesis-
intensification method for generation of novel and intensified solutions”, in preparation.
Garg, N., Woodley, J.M., Gani, R. and Kontogeorgis, G.M., 2019, “Sustainable solutions
by integrating process synthesis-intensification”, Computers and Chemical Engineering,
126, 499-519.
Page 44
PBS-Intensification: Definitions and Concepts
24
3.1. Definitions
3.1.1. General definitions
Binary Ratio Matrix
Binary ratio matrix is defined as the matrix of differences for considered or selected properties,
primarily as their ratio for all possible component binary pairs present in the problem.
Process synthesis
Process synthesis is defined as identification of an optimal processing route (base case) to convert
a set of raw materials into desired products from numerous feasible alternatives, subject to
process constraints and predefined performance criteria (adapted from Gani and Babi, 2014).
Direct and Indirect synthesis
Direct synthesis is defined as generation of process alternatives without any prior information of
an existing flowsheet (or base case) for a target production of desired product, while indirect
synthesis is defined as generation of process alternatives while improving upon an existing
process flowsheet or identification of completely new flowsheets with better performance.
Process intensification
Process intensification (PI) is defined as a significant improvement of a process at unit operation,
functional and/or phenomena level that can be obtained by integration of unit operations,
integration of physiochemical phenomena or functions or targeted enhancement of the
phenomena for a set of target operations (adapted from Lutze et al., 2013).
Phenomena based synthesis-intensification
Phenomena based process synthesis-intensification is defined as the generation (or synthesis) of
intensified process alternatives (includes existing and innovative) from the combination of
phenomena building blocks (PBBs) at the lowest scale (phenomena) that performs a task or a set
of tasks at the higher scale (adapted from Babi et al., 2015).
Sustainable process synthesis-intensification
Sustainable process synthesis-intensification is defined as the generation of more sustainable
process alternatives that correspond to improved values of a set of targeted performance
parameters obtained by integration of unit operations, integration of functions and phenomena’s
or targeted enhancement of the phenomena for a set of target operations (adapted from Lutze et
al., 2013 and Babi et al., 2015).
3.1.2. Phenomena related definitions
Phenomena or a Phenomena Building Block (PBB)
A phenomena or a phenomena building block is defined as the smallest unit at the lowest level
of aggregation that individually or in combination can perform a task or a part of a task in a
Page 45
3.2. Concept behind phenomena-based synthesis
25
chemical or a biochemical process. These phenomena are the ones that directly affect the driving
force for a task or a set of tasks to occur (adapted from Babi et al., 2015).
Simultaneous Phenomenon Building block (SPB)
A SPB is defined as the combination of one of more PBBs using predefined combination rules
and adjacency matrix that can perform a task or a part of task in a chemical or biochemical
process (adapted from Babi et al., 2015).
Principle PBBs
Principle PBBs are defined as a set of single or multiple non-repetitive PBBs that constitutively
defines a preliminary task or a set of task that they may perform. In other way, principle PBBs
can be called as an unstructured SPB.
Basic structure of SPBs
A basic structure is defined as a single or a combination of multiple SPBs using predefined
combination rules that can perform a targeted or a set of the targeted tasks in a chemical or
biochemical process (adapted from Babi et al., 2015).
Phenomena based synthesis
Phenomena based synthesis is defined as generation of flowsheet alternatives by combining
identified set of PBBs at the lowest level to form feasible SPBs that are further combined using
combinatorial rules to generate basic structures performing a certain task in a process which are
then translated to unit-operation as a part of different process alternatives.
3.2. Concept behind phenomena-based synthesis
Phenomena based synthesis is a rule-based approach and analogous to Computer Aided
Molecular Design (CAMD) (Harper and Gani, 2000). In phenomena based synthesis, innovative
process alternatives are generated by combining PBBs (analogous to atoms) at the lowest
aggregation level to generate SPBs (analogous to groups). These SPBs are combined to generate
basic structures (analogous to new feasible molecules) that perform a task or set of tasks that are
further translated to unit-operations constituting which flowsheet alternatives are synthesized.
These steps are constrained in a way that they satisfy predefined performance criteria similar to
CAMD where generated molecules satisfy a set of desired properties. An overview of the
comparison of phenomena-based synthesis to CAMD is given in Figure 3.1.
3.2.1. Phenomena building blocks (PBBs)
A chemical or biochemical process can be represented by combinations of different phenomena
occurring within the process in terms of mass, energy and momentum transfer (Lutze et al., 2013;
Babi et al., 2015). A comprehensive list along with new phenomena developed in this work is
shown in Table 3.1. They are divided into five categories (Mixing, Reaction, Mass transfer, Energy
Page 46
PBS-Intensification: Definitions and Concepts
26
transfer and Division) and are further classified based on possible phases and sources. An
example of a PBB is ‘R(L)’ where R denotes reaction while ‘L’ within brackets denotes the phase
in which reaction is taking place, immaterial of phases present within the system.
Figure 3.1: Comparison of phenomena based synthesis approach to CAMD
Table 3.1: List of Phenomena building blocks (PBBs) and their classification
Phenomena Building Block
(PBB) Category Class/Phase
Mixing (M) Mixing
V, L, S, VL, LS, VS, LL
Two-phase Mixing (2phM) LL, VL, LS, VS
Reaction (R) Reaction V, L, S, VL, LS, VS
Energy Supply (ES) Energy transfer C, H, D
Phase Contact (PC)
Mass transfer
VL, LS, LL, VS, SS
Phase Transition (PT) VL, MVL, LS, LL, MLL, VS, MVV
Phase Separation (PS) VL, LS, VS, VV, LL, SS
Dividing (D) Division -
Mixing (M) - Mixing of two or more streams, mixing of compounds occurring in a task (within
one phase or between several phases). For example, two liquid streams entering into the system
or a single stream consisting of multiple compounds.
Select PBBs
e.g. M(L), R(L), ES(C)
Generate SPBs
e.g. M(L)=ES(C), M(L)=R(L)=ES(C)
Combine SPBs to structures to
unit-ops
Screen feasible flowsheet
alternatives
Select atoms
e.g. C, H, O
Generate groups
e.g. CH2, CH3, OH
Combine groups to molecules
e.g. CH3-OH, CH2=CH2
Screen feasible candidates
e.g. CH3-OH
Select building
blocks
Generate
alternatives
Screen
alternatives
Connectivity rules
Page 47
3.2. Concept behind phenomena-based synthesis
27
Two-phase mixing (2phM) - If a task is driven by mixing of two-phase system, the mixing of
the two phases is required. For example, two phases can be two different phases like mixing of
liquid and gas or mixing of two different liquid phases like organic and aqueous phase.
Reaction (R) - If a reaction is taking place, i.e., raw materials entering the system are being
converted to products, a “R” PBB is required.
Energy Supply (ES) - If a single phase or multiple phases are present and enthalpy change occurs
due to direct (microwave, ultrasound etc.) or indirect (heating or cooling) energy source, “ES”
PBB is required. For example, cooling of a vapor stream using cooling water, heating of a liquid
stream using steam or use of microwave energy source.
Phase Contact (PC) – If two phases are present in a system and phase contact between them
drives the task, ‘PC’ phenomena is selected. For example, contact of ‘V’ and ‘L’ in distillation.
Phase Transition (PT) - If a transition from one phase to another is happening during a task,
then ‘PT’ phenomena is required. For example, transition of liquid to solid on cooling.
Phase separation (PS) – If separation of two phases is taking place, then a ‘PS’ phenomena is
required. For example, separation of solid and liquid or vapor and liquid.
Dividing (D) - If dividing of a stream is required with same set of properties, ‘D’ phenomena is
selected. For example, dividing a liquid stream into 3 streams.
Note: Here, V, L and S denote vapor, liquid and solid phases respectively, while C, H and D
denote cooling, heating and direct (microwave, ultrasound etc.) that are classes of energy supply
phenomena. MLL, MVL and MVV are special membrane phenomena for different phases. Among
these phenomena, Mixing (M) phenomena is always selected for any task defined. Also, the
entrance of two similar phases within a system is not considered as 2 phase mixing and any
notation of phase is not required for a two-phase mixing PBB within a simultaneous PBB.
3.2.2. Simultaneous phenomenon building block (SPB)
A single or multiple PBBs can be combined in different ways to generate SPB that can perform
an activity/action/task within a process. An SPB is read from left to right for a task or a set of
task. An order of PBBs within a SPB is as follows (not necessarily including all in a single SPB):
M = 2phM = R = ES = PC = PT = PS
Within a SPB, PBBs are separated with ‘=’ symbol denoting the occurrence of these phenomena
at the same time under same operating conditions. For example, consider M(VL), 2phM, PC(VL),
PT(VL), PS(VL) and R(VL) PBBs. Using these, several SPBs can be generated. An example being,
combining M(VL) and R(VL) phenomena, M(VL)=2phM=R(VL) SPB can be generated which is a
reaction SPB. Similarly, M(VL)=2phM=PC(VL)=PT(VL)=PS(VL) denotes a separation SPB, while
the reaction-separation SPB is denoted as M(VL)=2phM=R=PC(VL)=PT(VL)=PS(VL). The SPBs
Page 48
PBS-Intensification: Definitions and Concepts
28
constituting different PBBs may lead to generation of both feasible and infeasible SPBs. Thus, a
set of rules and adjacency matrix to generate feasible list of SPBs is presented in chapter 4.
3.2.3. Basic structure of SPBs
The combination of single or multiple SPBs form basic structure (s) that can perform a task or
set of tasks. These tasks when are further connected, form task-based flowsheets that are
translated to unit-operation. The SPB may or may not fulfill desired objective but a combination
of SPBs forming a basic structure should fulfill the desired objective or activity. For example,
consider a simple example of two SPBs shown in Table 3.2. These SPBs perform individual tasks.
But the combination of these forming a basic structure achieves the objective of a microwave
reactor (Table 3.3). The same task i.e. microwave reaction can also be performed by a single SPB
i.e. M=R=ES(D).
Table 3.2: List of SPBs for microwave reaction
SPB Task Inlet
M=R Reaction 1…..n(V, L…)
M=ES(D) Energy supply (direct) 1…..n(V, L…)
Table 3.3: Basic structure performing a task
Basic structure of SPBs Task Objective
Reaction in the presence
of microwave energy
source
Microwave
reaction
A single SPB can also perform multiple tasks but may not be sufficient to achieve the objective.
Thus SPBs performing multiple tasks can also be combined to form a basic structure that fulfills
the required objective. For example, consider a set of three SPBs as shown in Table 3.4.
Table 3.4: List of SPBs performing multiple tasks
SPB Task Inlet
M=2phM=PC(VL)=PT(VL)=PS(VL) Separation of compounds 1…..n(V, L, VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL) Cooling + Separation 1…..n(V, L, VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL) Heating + Separation 1…..n(V, L, VL)
The concept here is when selected SPBs are combined they fulfil multiple tasks reducing the
number of different unit-operations required to fulfil the objective of a unit-operation. The tasks
collectively performed by the basic structure is shown in Table 3.5.
M=R
M=ES(D)
Page 49
3.2. Concept behind phenomena-based synthesis
29
Table 3.5: Basic structure performing multiple tasks
Basic structure of SPBs Task Objective
- Cooling of vapor-liquid
Separation of vapor-liquid
- heating of vapor-liquid
Distillation
separation
Thus, when a basic structure performs multiple tasks, the search space of unit-operations is
expanded and can lead to the generation of novel and innovative solutions. A basic structure is
read upwards for an order of task performed by different SPBs not necessarily being the initiator
of the task.
3.2.4. Phenomena-based synthesis
An overview of basics behind phenomena-based synthesis is highlighted in Figure 3.2. The figure
shows example of a SPB within a basic structure and a PBB within an SPB. The basic structures
are translated to unit-operation.
Figure 3.2: An overview of phenomena based synthesis concept
Consider an example of an exothermic liquid phase reaction performing reaction task. It can be
described in terms of phenomena as ‘M(L)’ i.e. mixing of the liquid components in the reaction
‘R(L)’ where ‘L’ represents the reaction phase and ‘ES(C)’ is cooling required to remove the heat
generated because the reaction is exothermic. In the case of a microwave reactor, the energy
supply phenomena ‘ES(C)’ in exothermic reaction is replaced with ‘ES(D)’ that denotes special
energy sources like microwaves. Thus, using these PBBs simultaneously in combination for an
exothermic reaction task becomes a simultaneous phenomenon building block (SPB). Similarly,
R-Task M(L)=R(L)=ES(C)
M(L)=R(L)=ES(D)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R=ES(D)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
S-Task R-S-Task
R-Task
Basic structures combined to
generate new basic structures
Exothermic
reaction
Microwave
reaction
Distillation
Microwave reactive
distillation
Reactive
distillation
A ‘PBB’ A ‘SPB’ A ‘Basic structure’
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
Page 50
PBS-Intensification: Definitions and Concepts
30
for a distillation column separating two compounds, simultaneously occurring phenomena ‘M,
2phM, PC(VL), PT(VL), PS(VL)’ along with energy supply phenomena ‘ES(C)’ and ‘ES(H)’ are
selected. Using these phenomena different SPBs are generated that combine to form a basic
structure performing separation task which is translated to distillation.
Now to generate innovative solutions, consider the combination of basic structures for an
exothermic reaction (performing reaction task) and distillation (performing separation task)
using combinatorial algorithms, a new basic structure is generated that performs reaction and
separation task together. This new basic structure is translated to reactive distillation column.
Combining this new basic structure with another similar structure of distillation can be then
translated into a reactive divided wall column. In another case of microwave reaction and
distillation column, a new type of basic structure is generated that performs reaction and
separation task simultaneously with reaction taking place in presence of special energy source of
microwaves. This structure is then translated to microwave reactive distillation. Thus, in a similar
way using a set of algorithms, many novel and innovative solutions can be generated while
performing phenomena based synthesis.
3.3. Chapter summary
The chapter provides an essential idea about phenomena-based synthesis-intensification and
related terminologies. An extensive list of phenomena building block is defined which can be
combined in many ways at the lower scale to generate innovative solutions at the higher scale.
An example is provided in Figure 3.3 to give an overview of different scales. The phenomena-
based synthesis (PBS) is analogous to Computer-Aided Molecular Design (CAMD), as both these
approaches are multi-level and operate at different levels of aggregation.
Figure 3.3: Different level of aggregation for a reactive distillation column
PC
PT
PT
M, R
2phM
2phM
PC
PS
PS
ES(C)
ES(H)
R-S Task
PBBs
PBBs combined to SPBs
combined to basic structure
Basic structure
performing task
Basic structure
translated to unit-op
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R=PC(VL)=PT(VL)=PS(VL)
Page 51
3.3. Chapter summary
31
Chapter 4 PBS-Intensification: Methodology & Framework
Chapter outline:
4.1. Overview of methodology
4.2. Systematic framework
4.2.1. Stage I: Synthesis analysis
4.2.2. Stage II: Base case analysis
4.2.3. Stage III: Generation of feasible flowsheet alternatives
4.2.4. Stage IV: Ranking, analysis and comparison
4.3. Chapter summary
This journal article is partially based on this chapter:
Garg, N., Kontogeorgis, G.M., Gani, R. and Woodley, J.M., 2019, “A process synthesis-
intensification method for generation of novel and intensified solutions”, in preparation.
A systematic methodology to generate novel, innovative and intensified solutions
is presented in this chapter. The methodology is based on phenomena-based
synthesis that operates at the lower level of aggregation (phenomena) to move up
towards the unit-operation scale generating innovative solutions. Further, the
framework developed in this thesis is presented to perform phenomena-based
synthesis-intensification. The framework is capable of performing the synthesis-
intensification both for an existing process (indirect synthesis) and a completely
new problem (direct synthesis). There are 4 stages in the framework, where stage
1 performs problem analysis, stage 2 analyses the base case if exists, stage 3
performs phenomena-based synthesis and stage 4 ranks, validates and compares
generated alternatives. The framework is multiscale as it operates at phenomena,
task and unit-operation scale.
Page 52
PBS-Intensification: Methodology & Framework
32
4.1. Overview of methodology
The methodology developed for phenomena-based process synthesis-intensification consists of
13 steps across 4 stages, a set of algorithms, knowledge bases and associating tools. Associated
algorithms, knowledge bases and tools are presented in chapter 5. An overview of the framework
developed for the methodology is given in Figure 4.1.
Figure 4.1: An overview of phenomena based synthesis-intensification (Direct and indirect synthesis-intensification)
The methodology developed is not constrained to use an existing process or process flowsheet to
generate intensified solutions and is not restricted to the vapor-liquid systems limiting the
generation of wide range of solutions. The key features of the methodology include:
• Systematic direct and indirect synthesis of the novel, innovative and intensified process
alternatives without any a priori equipment postulation.
• Problem definition
• Problem analysis
• Reaction analysis
• Mixture analysis
I. Synthesis Analysis
• Mathematical combinatorial superstructure
• Phenomena superstructure
• Reduction of alternatives• Logical rules
• Feasibility rules
• Translation of phenomena to flowsheet alternatives
III. Generation of feasible flowsheet
alternatives
• Ranking of all alternatives
• Verification of the selected alternatives
• Detailed analysis and the comparison of top ranked alternatives
IV. Ranking, analysis and comparison
Mw
Tb
rg
Tm
Tc
Pc
ΔHr
Mv
Vvw
TtpPtp
Δ
Avw
PT(LL) 2phM
PS(LS)PT(LS)
PT(MVL) PS(VL)
PS(VL)
ES(D)
PT(VL)R(V)
PC(VL)
M(VL)
ES(C)
A B + C----B/C
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=R(V)=PT(VL)=PS(VL)
N=R(V)=ES(C)
M=PT(MVV)=PS(VV)
M=R=PC(VS)=PS(VS)*
A B + C
--ABC-- A/BC
A/CB
C/AB
C/BA
B/C
B/AC
B/CA
A/C
A/B
06
216
48
103
Total
alternatives
Before
combinationFor selected
phenomena
Mathematical
alternatives
• Generation of the task and phenomena based flowsheet
• Identification of desirable task and phenomena based on process hotspots
II. Base Case analysis
Base case
available?
Yes
Base case
available?
No
Page 53
4.2. Systematic framework
33
• Phenomena based synthesis (covering vapor, liquid and solid phases including special
energy sources like microwave, ultrasound etc.) based on physical properties and
thermodynamic insights affecting driving force performing a task or set of tasks.
• Novel phenomena-based superstructure approach to identify potentially feasible novel
solutions.
• Reduction of alternatives using feasibility and logical rules.
• Ranking of all the feasible alternatives to identify promising solutions that are further
analyzed in detail.
In stage I, the main objective is to set up the problem and perform synthesis analysis i.e. defining
problem, collecting reaction information, raw material and product data, mixture analysis and
generation of binary property ratio matrix. In stage II, the analysis of base case i.e. existing
process flowsheet (if available) is performed. Here, an initial list of tasks and phenomena along
with the desired list of phenomena mitigating the process hotspots from the base case is
identified. In case of no base case flowsheet, stage II is skipped. In stage III, firstly a mathematical
combinatorial superstructure of compounds is generated followed by identification of principle
PBBs. Further, using the total list of phenomena and thermodynamic-property algorithms,
phenomena-based superstructure is generated. In this phenomena-based superstructure, the
alternatives are reduced by following a set of the logical and the feasibility rules. The reduced
superstructure consisting of principle PBBs is then translated to basic structures and thus using
combinatorial algorithms and translation of the basic structures to unit operations, potential
flowsheet alternatives are generated. Finally, in stage IV, selected flowsheet alternatives are
ranked based on Enthalpy Index (EI) to identify top alternatives which are further analyzed to
identify potentially innovative and intensified solutions.
4.2. Systematic framework
The detailed workflow of the developed systematic framework for phenomena-based synthesis-
intensification method is shown in Figure 4.2. The framework consists of 13 steps within 4 stages
operating at the phenomena scale, task scale and unit-operation scale.
4.2.1. Stage I: Synthesis analysis (step 1-2)
Objective – The objective of stage I is to set up, analyze and collect information about the
problem in order to synthesize innovative and intensified solutions in further steps of stage II,
III and IV.
Information required
The information required to accomplish the objective is as follows:
- Problem type (direct or indirect)
Page 54
PBS-Intensification: Methodology & Framework
34
Figure 4.2: Systematic framework for direct and indirect PBS-intensification
I. Synthesis Analysis
III. Generation of feasible flowsheet alternatives
IV. Ranking, analysis & comparison
Step 5: Generation of mathematical combinatoral
superstructure of compounds
Innovative and intensified
solutions
General workflowMethods and Tools Information flow
II. Base case Analysis
YES
NO
Unit-op to task and phenomena
database
Process hotspots to additional
task and phenomena database
Base case
Flowsheet?
Product info, input and output
compounds, reaction data and
conditions, flowrate
Literature search, ICAS
database
Properties database (ICAS),
Literature, AzeoPro, ProPed
Step 1: Problem definition
Step 2: Problem Analysis
Step 6: Identification of principle PBBs
Step 7: Generation of list of feasible SPBs
Step 9: Reduction of alterantives and generation
of basic strucutres
Information from step-1
Step 10: Combination of basic structures to
generate flowsheet alternatives
Step 3: Generation of task and phenomena based
flowsheet
Step 4: Identification of additional task and
phenomena
Step 11: Translation of the basic structures to
unit-operation
Step 12: Ranking and verification of generated
flowsheet alterantives
Mixture phase, Binary ratio
matrix, azeotropes, eutectic
points, miscibility gaps
Logical and feasibility rules
Combination rules
ICAS-MoT, PRO/IITM
, Aspen
PlusTM
SPBs calculation and
Combination rules
Translation of property to
phenomena database
Translation of basic structure to
unit-op database
Base case flowsheet
Process hotspots
Task and phenomena (PBB)
based flowsheet
Information from step-2
Number of compounds
Total list of PBBs
List of feasible SPBs
Phenomena based
superstrucutre
Generated flowsheet
alternatives
Step 8: Generation of phenomena based
superstrucutre
Step 13: Analysis and comparison of selected
flowsheet alterantivesECON, LCSoft, SustainPro
Selected flowsheet alternatives
Knowledge base
Algorithm
Outflow
Steps
Inflow
Page 55
4.2. Systematic framework
35
- Information about product(s) and raw material(s)
- Reaction(s) to convert raw material into desired product(s)
- Operating conditions of the reaction
- Production capacity or flow rate
- Pure component and mixture properties
- Binary ratio matrix
Algorithms needed
- Algorithm A1.1 (section 5.2.1)
Steps/Action
Step 1: Problem definition
The objective of this step is to define the problem and the performance criteria to generate novel,
innovative and intensified solutions.
• S1.1. Problem type
The problem can be of two type i.e. direct or indirect synthesis-intensification. A base
case flowsheet is known for indirect synthesis and then the problem is defined as:
generation of more economical and sustainable solutions than an existing process
flowsheet based on predefined performance criteria. While, for direct synthesis no such
information is available and the problem definition is to generate novel, innovative and
intensified flowsheet alternatives for the production of desired product using selected
raw materials matching the predefined performance criteria.
• S1.2. Information collection
Collect reaction information or perform a literature/online search to identify possible
reaction pathways for producing the desired product using selected raw materials. The
keywords related to the product and raw material can be used for easy search. ProCARPS
(Cignitti, 2014), a reaction path synthesis tool can also be used to identify the potential
reaction routes. Also, retrieve the reaction conditions. Having the reaction, only input
and output components are known for a new synthesis-intensification problem (direct
synthesis). Thus, the task is to determine correct, innovative and intensified sequence of
unit operations that will produce the desired product matching the performance targets.
In addition, for retrofit problems or an indirect synthesis problem where one seeks to
improve upon an existing process flowsheet or find a completely new process flowsheet
with better performance than an existing alternative, step S1.2 includes the collection of
information about reaction from a base case, with raw material inlets, and the desired
product outlets.
The information flow of step 1 is illustrated in Figure 4.3.
Page 56
PBS-Intensification: Methodology & Framework
36
Figure 4.3: Information flow for step 1
Step 2: Problem analysis
In this step the problem is analyzed in terms of reaction and mixture analysis including pure
component property analysis for the compounds involved in the system.
• S2.1. Reaction analysis
For the identified reaction pathway retrieve conversion data and the reaction phase. The
phase can be solid, liquid and vapor or a combination of above. Also identify the catalyst
(if used in the reaction), that can be heterogeneous or homogenous along with reaction
equilibrium data to identify if the reaction is an equilibrium or forward reaction.
Additionally, identify the reaction kinetics data as per availability. Once the required
information is collected, the reaction is analyzed as follows:
o Identify product(s) and by-product(s) phase involved in the system. Then, calculate
the heat of reaction as follows:
∆Hrxn = ∑ ∆vp ∗ ∆Hf (products) − ∑ ∆vr ∗ ∆Hf (reactants)
(4.1)
Here, ∆Hrxn = Heat of reaction.
vp and vr are the stoichiometric coefficient of the reactant and the product from
the balanced reaction
Hf = Heat of formation of the reactant or product.
o Define the reaction system that can be either one or a combination:
- Forward reaction
- Reversible reaction
o Using heat of reaction data, state the reaction type as follows:
- For ∆Hrxn< 0, reaction is defined as exothermic
- For ∆Hrxn> 0, reaction is defined as endothermic
• S2.2. Mixture analysis
In the mixture analysis task, following two types of analysis are performed for all the
components present in the defined problem. This is to generate information/data for
identification of feasible phenomena that are required to achieve the desired task.
Input information
Raw materials, products,
production rate, reaction,
Pressure, Temperature
Methods/Tools used
Literature search,
ICAS database
Output information
Inlet and outlet
information, Performance
criteria
Page 57
4.2. Systematic framework
37
o Pure component analysis: This section of the analysis is performed by collecting
the pure component property data (Table 4.1) from the literature search or ICAS
database (Gani et al. 1997; Gani 2002). The required property data missing for
compounds or new compounds can be calculated using ProPred (property prediction
software) which is available in Integrated Computer Aided System (ICAS) (Gani et al.
1997; Gani 2002). Thus, based on collected property information, the binary ratio
matrix is generated by using algorithm A1.1.
o Mixture property analysis: The mixture property analysis is performed by starting
with identifying the mixture state or phase (after reaction) followed by identifying
the state of pure components at the reference temperature (mixture conditions and
ambient conditions). Then the analysis is performed in terms of the binary pairs of
all the components that are identified in step 1. For each binary pair, a list of analysis
is performed to determine presence of azeotropes, eutectic points, miscibility gaps
i.e. liquid-liquid phase splits or potential MSA’s (mass separation agents) if required.
Azeotropes can be identified by plotting VLE phase diagram using adequate
thermodynamic model. If an azeotrope exists, its pressure sensitivity should also be
checked by varying the pressure for example from 1 to 10 bar and see if the VLE plot
shifts. A hint of an azeotrope between the binary pair can also be identified from
binary ratio of boiling point i.e. if the boiling point ratio is close to unity, then an
azeotrope may exist. Azeopro (Azeotrope analysis toolbox from ICAS), can be used
to identify azeotropes present in the system. Miscibility gap can be hinted from
octanol-water coefficient being much greater than 1 while, eutectic point can be
identified by plotting SLE phase diagrams.
Table 4.1: Selected list of properties for mixture analysis task
Property Symbol UOM
Molecular weight Mw g/mol
Normal Boiling point Tb K
Radius of gyration rg nm
Melting Point Tm K
Solubility parameter δ √(kJ/m3)
vander Waals volume Vvw m3/kmol
Vapor pressure Pvap Pa
Molar volume Mv m3/kmol
Heat of vaporization Hvap J/mol
Dipole moment dm Debye
Heat of Fusion at Tm Hfus kJ/kmol
Diffusivity α m2/s
Page 58
PBS-Intensification: Methodology & Framework
38
Surface tension γ J/m2
Critical temperature Tc K
Ionic charge - -
Kinetic diameter d pm
Molecular diameter σ pm
Critical pressure Pc bar
Heat of Formation Hf kJ/kmol
vander Waals area Avw m2/kmol
Octanol water partition coefficient Kow -
Standard Net Heat of combustion Hcomb MJ/kmol
Acentric factor ω -
Critical volume Vc m3/kmol
Critical compressibility factor Zc -
Triple point temp Ttp K
Triple point pressure Ptp Pa
Ideal Gas Gibbs Energy of
Formation Gf kJ/kmol
Ideal Gas Absolute Entropy SIG kJ/(kmol · K)
Flash point - K
The information flow of step 2 is illustrated in Figure 4.4.
Figure 4.4: Information flow for step 2
4.2.2. Stage II: Base case analysis (step 3-4)
Objective – The objective of stage II is to analyze the existing process flowsheet (base case) in
terms of existing task and phenomena, identify additional task and principle phenomena
mitigating the process hotspots and further set design targets that needs to be achieved while
generating innovative and intensified flowsheet alternatives.
Note: This stage is only performed in case of availability of existing process flowsheet and the
objective of the problem is to find retrofit solutions or to identify more sustainable and economic
intensified process alternatives.
Input information
List of components and its
information, reaction
information
Methods/Tools used
Pure component properties,
Literature search,
ICAS database, Azeopro,
ProPred, ProCAMD,
Output information
Binary ratio matrix,
azeotropes, miscibility
gaps, eutectic points
Page 59
4.2. Systematic framework
39
Information required
The information required to accomplish the objective is as follows:
- Existing process flowsheet (base case)
- Process hotspots
- List of task and phenomena
- Design targets
Algorithms needed
- Algorithms A2.1, A2.2 and A2.3 (section 5.2.2)
Knowledge base needed
- Knowledge base KB2.1 and KB2.2 (Appendix C.1 and C.2)
Steps/Action
Step 3: Generation of task and phenomena based flowsheet
The objective of step 3 is to generate task and phenomena based flowsheet by identifying the
tasks and initial search space of phenomena that are responsible for existing unit-operations.
• S3.1. Task based flowsheet
The first action of this step is to translate the base case flowsheet into a task-based
flowsheet (for example a reactor unit operation performs a reaction task, or a distillation
column performs a separation task). Apply algorithm A2.1 that uses the knowledge base
KB2.1 to generate task based flowsheet.
• S3.2. Phenomena based flowsheet
The base case flowsheet is further translated to phenomena-based flowsheet to identify
an initial list of principle PBBs. Apply algorithm A2.2 that uses knowledge base KB2.1 to
generate phenomena based flowsheet. Identified list of phenomena in this step is the
initial search space and is further used in stage III.
The information flow of step 3 is illustrated in Figure 4.5.
Figure 4.5: Information flow for step 3
Input information
Unit-operation based
flowsheet
Methods/Tools used
Unit-operation to task and
phenomena database
Output information
Initial list of task and
phenomena
Page 60
PBS-Intensification: Methodology & Framework
40
Step 4: Identification of additional task and phenomena
In this step, additional set of tasks and phenomena are identified to overcome the process
hotspots for an existing process flowsheet that expands the current search space. Additionally,
design targets are identified to be achieved while generating more economic, sustainable,
innovative and intensified solutions for an existing process.
• S4.1. Process hotspots and design targets
The process hotspots for the base case flowsheet, are identified by performing economic,
sustainability and LCA analysis based on a matrix developed by Babi et al. (2015). The
matrix is presented in Appendix A. The simulation data or real plant data in terms of
mass and energy balance is required to perform above analysis. If both simulation data
and real plant data is not available for the base case flowsheet, the required data can be
generated by following the systematic approach by Babi, (2015). The economic analysis
of the existing process includes utility cost, operational and capital costs and can be
performed using ECON (Saengwirun, 2011) if a computer-aided tool is not available. The
sustainability indicators like MVA (Material Value Added), EWC (Energy and waste cost)
and TVA (Total value added) are calculated using SustainPro (Carvalho et al., 2013).
Additionally, LCA analysis (LCSoft) (Kalakul et al., 2014) is performed to calculate carbon
footprint and other environmental indicators (like Global Warming Potential (GWP),
Ozone Depleting Potential (ODP), Human Toxicity Potential by Ingestion (HTPI),
Photochemical Oxidation Potential (PCOP) to name a few). Once this information is
available, the matrix developed by Babi et al. (2015) (Appendix A) is used to translate the
indicator values to the process hotspots.
The process hotspots are further used to set design targets additional to the objective set
for the problem (for example lesser number of equipment, waste minimization, reduction
in loss of raw material). These design targets are required to be achieved while generating
non-trade off solutions for the base case. An indicative list to identify the design targets
using process hotspots is presented in Appendix B (Babi et al., 2015). These design targets
are compared for the base case with the selected set of alternatives in stage IV.
• S4.2. Additional task and phenomena
A list of additional tasks and desirable phenomena are identified using algorithm A2.3
and knowledge base KB2.2 based on identified process hotspots for existing process.
These phenomena are desirable as they may assist in overcoming identified bottlenecks.
They are also beneficial as it expands the existing limited search space, therefore
providing an option to innovate and improve on base case flowsheet or generate
completely novel and innovative flowsheet alternatives.
The information flow of step 4 is illustrated in Figure 4.6.
Page 61
4.2. Systematic framework
41
Figure 4.6: Information flow for step 4
4.2.3. Stage III: Generation of feasible flowsheet alternatives (step 5-11)
Objective – The objective of stage III is to generate novel, innovative and intensified feasible
flowsheet alternatives by performing phenomena based synthesis. This stage operates at different
levels i.e. phenomena, task and unit-operation starting from phenomena level where different
phenomena are identified to perform tasks that are further translated to unit-operations.
Information required
The information required to accomplish the objective is as follows:
- List of compounds and binary pairs
- Binary ratio matrix
- Mathematical combinatorial superstructure of compounds
- Principle PBBs for all binary pairs
- Phenomena based superstructure
- Logical and feasibility rules
- Combination rules
Algorithms needed
- Algorithms A3.1, A3.2, A3.3, A3.4, A3.5, A3.6 and A3.7 (section 5.2.3)
Knowledge base needed
- Knowledge base KB3.1 and KB3.2 (Appendix C.3 and C.4)
Steps/Action
Step 5: Generation of mathematical combinatorial superstructure of compounds
In this step, the mathematical combinatorial superstructure of compounds is generated that
consists of all the alternatives mathematically possible for all the compounds present in the
problem. Here, any phase or conditions of the compound is ignored to cover the whole search
space with the possibility to separate all the compounds. This superstructure is generated using
Input information
Process hotspots
Methods/Tools used
Process hotspots to
desirable task and
phenomena database
Output information
Design targets and
additional task and
phenomena
Page 62
PBS-Intensification: Methodology & Framework
42
algorithm A3.1. The only information required for this step is the number of components present
in the system.
Step 6: Identification of principle PPB’s
The objective of this step is to identify a set of principle PBBs for all the identified binary pairs
and tasks. The list of principle PBBs are identified using knowledge base KB3.1 and algorithm
A3.2. The knowledge base is developed on the basis of physical insights based method (Jaksland
et al., 1995) and thermodynamic insights that transform the pure and mixture property analysis
into a set of phenomena that may assist in achieving the required task. These identified
phenomena are the ones that drive the task. The physical insights method is based on the fact
that, a binary pair of component can be separated based on binary ratios above threshold values
of one or more pure component properties. These set of properties are explored in terms of
phenomena to generate the knowledge base and thus identify the feasible set of phenomena.
Also, using thermodynamics insights i.e. by looking at energy requirement in a reaction task or
SLE, VLE and LLE plots for a binary pair, a set of phenomena database is established that can
perform the task.
The principle PBBs identified in this step are combined with the PBBs identified from stage II
constituting the complete list of phenomena for each considered case. The information flow of
step 6 is illustrated in Figure 4.7.
Figure 4.7: Information flow for step 6
Step 7: Generation of list of feasible SPBs
In this step, a list of feasible SPBs is generated based on total number of PBBs that are identified
from step 6 in stage III in addition to the one’s identified in stage II, if a base case is available. ‘D’
phenomena is always selected as an additional PBB and added to the identified list.
• S7.1. Operating window for identified PBBs
The first action in step 7 is to identify the operating window for each of the identified
PBBs. The operating window is the thermodynamical limitation for all the identified
phenomena as their operational constraint. A table to identify the operating window for
different PBBs is given in Table 4.2.
Input information
List of components, binary
ratio matrix, mixture
property analysis
Methods/Tools used
Database translating pure
and mixture property
analysis to phenomena
Output information
List of principle PBBs for
all the binary pairs
Page 63
4.2. Systematic framework
43
Table 4.2: Operating window guide for identified PBBs (adapted from Babi et al., 2015)
Task PBB Operating
variables
Properties to
be checked Example
Reaction R T, P Tb, Tazeotrope,
Tm, Teut
Single phase (L),
P-Reaction pressure (reported in literature)
T-Lowest boiling compound or minimum
boiling azeotrope
T-Highest boiling compound or maximum
boiling azeotrope
Multiple phase (V-L)
P-Reaction pressure (reported in literature)
T-Lowest boiling compound or minimum
boiling azeotrope
T-Highest boiling compound or maximum
boiling azeotrope
Mixing M T, P Tb, Tazeotrope,
Tm, Teut
Liquid Mixing: T- Lowest melting compound
Liquid Mixing: T- Highest boiling compound
Vapor Mixing: T-Lowest boiling compound
or minimum boiling azeotrope
Two-phase mixing 2phM T, P Tb, Tazeotrope,
Tm, Teut
T-Lowest boiling compound or minimum
boiling azeotrope (for V-L systems)
T-Highest boiling compound or maximum
boiling azeotrope(for V-L systems)
T-Lowest melting compound or eutectic
point (for L-S systems)
T-Highest melting compound or eutectic
point (for L-S systems)
Energy Supply ES T TST, TTD -
Phase Contact PC - - Phases need to be present
Phase Transition PT
T, P
Tb, Tazeotrope,
Tm, Teut
T-Lowest boiling compound or minimum
boiling azeotrope (for V-L systems)
T-Highest boiling compound or maximum
boiling azeotrope(for V-L systems)
T-Lowest melting compound or eutectic
point (for L-S systems)
T-Highest melting compound or eutectic
point (for L-S systems)
Affinity - Component affinity (MVL, MVV, MLL)
Phase Separation PS - - Phases need to be present
Dividing D - - -
Page 64
4.2. Systematic framework
• S7.2. Feasible SPBs
The maximum number of possible SPBs (feasible and infeasible) from which a list of
feasible SPBs is generated as following:
o Maximum number of SPBs (feasible and infeasible): The maximum number of
SPBs that can be generated from the identified search space of PBBs is calculated
using the following equation (adapted from Lutze et al., 2013).
nSPBMax = ∑ [(nPBB − 1)!
(nPBB − k − 1)! k!]
nPBBMax
k=1
+ 1 (4.2)
nSPBMax is total number of possible SPBs,
nPBB is the total number of identified PBBs,
nPBBMax is the maximum number of PBBs within a SPB.
In equation 4.2, nPBBMax i.e. the maximum number of PBBs possible within a single
SPB can be 7 which is developed from the basic form of all the phenomena in Table
3.1 in chapter 3. Dividing phenomena is not included in nPBBMax, as it is considered
as a single SPB.
o Generation and screening of feasible SPBs: The feasible list of SPBs is generated
by following a set of rules. These rules are as follows:
- Maximum possible PBBs within a SPB and their order should be as follows:
M = 2phM = R = ES = PC = PT = PS
- A feasible SPB consisting of mass transfer PBBs should have same phase and
associating mixing phenomena having same or similar phase to mass transfer
PBBs.
- The rule regarding the maximum number of different mass transfer PBBs within
a SPB if present is as follows:
∑ PBBPC = ∑ PBBPT = ∑ PBBPS = 1
- The rule regarding the energy supply PBBs within a SPB if present is as follows:
∑ PBBES(C) + ∑ PBBES(H) + ∑ PBBES(D) = 1
- A PBB cannot be repeated within a SPB.
An indicative list of the building blocks to generate SPBs is shown in Table 4.3.
Further, generate the list of feasible SPBs using the adjacency matrix that consists of
complete list of phenomena shown in Table 4.4.
Page 65
4.2. Systematic framework
45
Table 4.3: Building blocks to generate SPBs (adapted from Babi et al., 2015)
No. SPB Building
block Inlet Task
1 M=ES(C) 1…n(V, L, S,…..) Performs cooling
2 M=ES(H) 1…n(V, L, S,…..) Performs heating
3 M=ES(D) 1…n(V, L, S,…..) Special energy supply
4 M=R 1…n(V, L, S,…..) Performs a reaction without any energy supply
5 M=2phM 1…n(V, L, S,…..) Performs mixing of two phases
6 =PC=PS 1…n(V, L, S,…..) Performs separation of two phases
7 =PC=PT 1…n(V, L, S,…..) Performs contact and phase creation
8 =PT=PS 1…n(V, L, S,…..) Performs separation of two phases
9 =PC=PT=PS 1…n(V, L, S,…..) Performs separation of two phases
10 D 1…n(V, L, S,…..) Performs division of stream
The information flow of step 7 is illustrated in Figure 4.8.
Figure 4.8: Information flow for step 7
Step 8: Generation of phenomena based superstructure
The phenomena based superstructure is generated by combining mathematical combinatorial
superstructure of compounds generated in step 5 and the list of principle PBBs identified in step
6. The algorithm to generate the phenomena based superstructure is given in section A3.3.
Step 9: Reduction of alternatives and generation of basic structures
This step of the framework consists of two parts i.e. reduction of the phenomena based
superstructure and then translation of principle PBBs to basic structures from the set of feasible
SPBs generated in step 7. These are as follows:
• S9.1. Reduction of alternatives
The phenomena based superstructure generated in step 8 consists of all feasible and
infeasible alternatives. This superstructure is thus reduced to remove alternatives that
Input information
List of identified
phenomena building blocks
(PBBs)
Methods/Tools used
Combination rules for
PBBs to SPBs
Output information
Operating window for all
PBB s, list of feasible
SPBs
Page 66
PBS-Intensification: Methodology & Framework
46
are infeasible and illogical using logical and feasibility rules. Follow algorithm A3.4 to
perform this action.
o Feasibility rules: The feasibility rules are based on task performed and the principle
PBBs identified in previous steps. The task based rules are developed using heuristics
(Douglas, 1985) i.e. separation considerations based on phases present in the system.
This action primarily assists in reduction of the superstructure size by removing sub
superstructures. Further, using physical property insights, infeasible set of principle
PBBs for every binary pair present in the system are removed.
o Logical rules: The logical rules are based on inlet and outlet conditions of PBBs
involved in the selected binary pair that may or may not be an inlet to the adjacent
task. The feed conditions are checked both at ambient and original conditions.
• S9.2. Generation of basic structures
The next action in step 9 is to transform the principle PBBs into basic structures. The
SPBs generated in step 7 are used to identify feasible set of basic structures representing
principle PBBs. These generated basic structures are one’s that can potentially complete
required task. Use algorithm A3.5 to complete this action of step 9. The superstructure
consisting of basic structures is level 1 phenomena-based superstructure.
The information flow of step 9 is illustrated in Figure 4.9.
Figure 4.9: Information flow for step 9
Step 10: Combination of basic structures to generate flowsheet alternatives
The objective of step 10 is to generate level 2 and level 3 phenomena based superstructures. This
is done by considering the combination of basic structures across adjacent tasks to generate new
basic structures performing integrated tasks i.e. multiple tasks. The algorithm required to
generate these set of superstructures is presented in A3.6. The level 2 superstructure is generated
by combining basic structures performing adjacent tasks in level 1 superstructure. Further, level
3 superstructure is generated by combining structures generated at level 2 to generate innovative
solutions. At both the levels, the combinations are performed across reaction-separation and
separation-separation tasks.
Input information
Phenomena based
superstructure
Methods/Tools used
Reduction rules
(feasibility and logical),
List of feasible SPBs
Output information
Level 1 phenomena based
superstrucutre
Page 67
4.2
. S
yste
mat
ic f
ram
ewo
rk
Ta
ble
4.4
: A
dja
cen
cy m
atr
ix f
or
com
ple
te l
ist
of
PB
Bs
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
PBB
M
R
2phM
PC(VL)
PC(LS)
PC(LL)
PC(VS)
PC(SS)
PT(VL)
PT(LL)
PT(LS)
PT(VS)
PT(PVL)
PT(VV)
PT(M
LL)
PS(VL)
PS(VV)
PS(LL)
PS(LS)
PS(VS)
PS(SS)
ES(C)
ES(H)
ES(D)
D
M
-+
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
-
R
-+
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ +
+ -
2phM
-
+ +
+ +
- +
+ +
+ -
- -
+ +
+ +
+ -
+ +
+ -
PC(VL)
-
- -
- -
+ -
- -
+ +
+ +
- -
- -
-+
+ +
-
PC(LS)
-
- -
- -
- -
- -
- -
- -
- -
- -
+ +
+ -
PC(LL)
-
- -
- +
--
- -
+ -
- +
- -
- +
+ +
-
PC(VS)
-
- -
- -
+ -
- -
- -
- -
+ -
+ +
+ -
PC(SS)
-
- -
- -
- -
- -
- -
- -
+ +
+ +
-
PT(VL)
-
- -
- -
- -
+ -
- -
- -
+ +
+ -
PT(LL)
-
- -
- -
- -
- +
--
-+
+ +
-
PT(LS)
-
- -
- -
- -
- +
--
+ +
+ -
PT(VS)
-
- -
- -
- -
- +
-+
+ +
-
PT(M
VL)
-
- -
+ -
- -
- -
- -
- -
PT(M
VV)
- -
- +
--
- -
- -
- -
PT(M
LL)
- -
- +
--
- -
- -
-
PS(VL)
-
- -
- -
- +
+ +
-
PS(VV)
- -
- -
-+
-+
-
PS(LL)
- -
- -
+ +
+ -
PS(LS)
- -
- +
+ +
-
PS(VS)
-
- +
+ +
-
PS(SS)
-+
+ +
-
ES(C)
-+
+ -
ES(H)
-+
-
ES(D)
--
D
-
Page 68
4.2. Systematic framework
The information flow of step 10 is illustrated in Figure 4.10.
Figure 4.10: Information flow for step 10
Step 11: Translation of the basic structures to unit-operation
The objective of step 11 is to generate unit-operation based flowsheet alternatives. These are
generated by translating the basic structure in the phenomena based superstructures at level 1, 2
and 3. These flowsheet alternatives are one’s that perform the required tasks to obtain desired
products. The basic structures are translated and thus flowsheet alternatives at unit-operation
scale are generated using algorithm A3.7 and KB3.2 given in chapter 5.
4.2.4. Stage IV: Ranking, analysis and comparison (step 12-13)
Objective – The objective of stage IV is to rank the alternatives generated in stage III, analyze
and then compare the top ranked or selected alternatives to find the potential solutions. Also, in
case of an existing base case, the generated alternatives are compared in order to verify if set
design targets are achieved.
Information required
The information required to accomplish the objective is as follows:
- Generated flowsheet alternatives
- Enthalpy Index (EI) for all the alternatives
- Performance indicators value
Algorithms needed
- Algorithm A4.1 (section 5.2.4)
Steps/Action
Step 12: Ranking and verification of generated flowsheet alternatives
In this step, the feasible flowsheet alternatives generated in stage III are in order to identify the
top alternatives and are then verified using model analysis or by performing simulations to
retrieve mass and energy balance data.
Input information
Level 1 phenomena based
superstrucutre
Methods/Tools used
Combinatorial rules for
basic structures
Output information
Level 2 and 3 phenomena
based superstrucutre
Page 69
4.2. Systematic framework
49
• S12.1. Ranking of unit-operation based flowsheet alternatives
The flowsheet alternatives are ranked using Enthalpy Index (EI). EI is the modular ratio
of lowest enthalpy for a flowsheet alternative to the enthalpy of considered alternative.
Ranking is done in order to quickly identify and screen top ranked alternatives as it is not
logical to perform analysis for all the flowsheet options. These alternatives may include
completely novel and innovative alternatives; thus, specific shortcut models are not
possible to generate apriori. Algorithm A4.1 is developed to generate the ranking.
• S12.2. Verification of selected flowsheet alternatives
The top ranked or selected alternatives are then verified by performing modelling or
simulation. This is performed in order to understand novel intensified unit-operations
that may or may not be involved in the selected flowsheet alternatives. Some of the
models for intensified unit-operations like reactive distillation, reactive flash can be
retrieved from ICAS-MoT for further analysis (Gani et al., 1997; Fedorova et al., 2014). In
case of presence of membrane or adsorptions systems that uses any separating agent,
verification is performed in terms of availability of real data in literature that can be used
to perform detailed analysis. The alternatives for which the real data is not available are
not chosen for further analysis and thus, options further in the ranking are selected.
Finally, for verified alternatives, the mass and energy balance data is retrieved.
The information flow of step 12 is illustrated in Figure 4.11.
Figure 4.11: Information flow for step 12
Step 13: Analysis and comparison of selected flowsheet alternatives
The objective of this final step is to analyze and compare the selected alternatives in terms of
economics, sustainability and life cycle assessment. Additionally, it is performed for an indirect
synthesis problem to calculate the performance indicator values that are used to compare the
base case with the selected flowsheet alternatives in terms of pre-defined performance criteria.
• S13.1. Analysis of selected alternatives
The mass and energy balance retrieved from step 12 is used to perform economics
analysis, sustainability analysis and life cycle assessment. The analysis can be performed
using the tools used in step S4.1 (ECON for economic analysis, SustainPro for the
Input information
Unit-operation based
flowsheet alternatives
Methods/Tools used
Enthalpy Index (EI),
Model based analysis or
simulation
Output information
Top ranked alternatives,
Mass and energy balance
data
Page 70
PBS-Intensification: Methodology & Framework
50
sustainability analysis while LCSoft for LCA analysis). The performance indicator values
are calculated for all the selected alternatives based on above analysis.
• S13.2. Comparison of selected alternatives
The comparison is made for the alternatives independent of the problem type i.e. direct
or indirect synthesis-intensification. In case of a direct synthesis-intensification problem,
the comparison is made among the selected alternatives while in case of an indirect
synthesis-intensification problem, for an innovative or novel intensified alternative to be
a non-trade off solution i.e. more sustainable and economic, it must show improvements
(or no change) with respect to all the performance criteria parameters. Also, perform a
check for both the problem types, if the design targets are met.
Thus, the alternatives that match the performance criteria and design targets are potential novel,
innovative and intensified solutions for the considered problem.
The information flow of step 13 is illustrated in Figure 4.12.
Figure 4.12: Information flow for step 13
4.3. Chapter summary
The developed framework for phenomena based synthesis-intensification has been presented
step by step to generate novel, innovative and intensified process flowsheet alternatives. The
chapter also presented detailed workflow, information flow and methods needed to perform
every step. The key elements of the developed framework are phenomena-based representation
for a superstructure consisting of all the alternatives and systematic algorithms to carry out
different steps (presented in detail in chapter 5). Further, it has been shown that the framework
is not only capable of performing indirect synthesis to generate better alternatives in terms of
economy, sustainability and LCA but can also perform direct synthesis-intensification.
Input information
Mass and energy balance
data for selected
alterantives
Methods/Tools used
ECON, LCSoft, SustainPro
Output information
Performance indicator
values, Potential solutions
Page 71
4.3. Chapter summary
51
Chapter 5 PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
Chapter outline:
5.1. Overview
5.2. Algorithms
5.2.1. Algorithms: Stage I
5.2.2. Algorithms: Stage II
5.2.3. Algorithms: Stage III
5.2.4. Algorithms: Stage IV
5.3. Knowledge bases
5.4. Supporting tools
5.5. Chapter summary
This journal article is partially based on this chapter:
Garg, N., Kontogeorgis, G.M., Gani, R. and Woodley, J.M., 2019, “A process synthesis-
intensification method for generation of novel and intensified solutions”, in preparation.
This chapter presents the detailed algorithms, knowledge bases and associated
tools required for the phenomena-based synthesis-intensification. Algorithms
operates at unit-operation, task and phenomena scale. The objective of Stage I
algorithm is to generate the binary ratio matrix. Stage II algorithms are used to
identify the initial search space of phenomena alongside additional phenomena
mitigating process hotspots. The objective of stage III algorithms is to identify
desirable PBBs combined using combinatorial algorithms to generate feasible
basic structures constituting SPBs, performing desired task that are further
combined to generate new and innovative solutions. At stage IV, algorithm is used
to rank the alternatives in order to identify top flowsheets for further analysis. The
knowledge bases developed and other supporting tools that assists algorithms and
steps to complete their objectives across all the stages are also presented.
Page 72
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
52
5.1. Overview
The framework performing direct and indirect phenomena-based synthesis-intensification
consists of 12 algorithms and 4 knowledge bases across 4 stages. These algorithms and knowledge
bases are supported by computer-aided tools. An overview of all algorithms, knowledge bases
and supporting tools is given in Tables 5.1, 5.2 and 5.3 respectively.
Table 5.1: List of algorithms developed in the framework
Sr. No.
Algorithm Stage/Step Objective
1 A1.1 I/2 Transform the base case flowsheet to a task-based flowsheet
2 A2.1 II/3 Identify tasks in the base case flowsheet and transform the base case flowsheet to a phenomena-based flowsheet
3 A2.2 II/3 Identify PBBs in the base case flowsheet and transform a task-based and base case flowsheet to a phenomena-based flowsheet
4 A2.3 II/4 Identify additional task and phenomena based on identified process hotspots of base case
5 A3.1 III/5 Generate a mathematical combinatorial superstructure of compounds
6 A3.2 III/6 Identify list of principle PBBs for all the binary pairs
7 A3.3 III/7 Generate phenomena based superstructure
8 A3.4 III/8 Reduce alternatives within phenomena based superstructure
9 A3.5 III/9 Transform principle PBBs to basic structures using list of feasible SPBs
10 A3.6 III/10 Generate alternatives by combining basic structures
11 A3.7 III/11 Translate basic structures into unit operations to generate flowsheet alternatives
12 A4.1 IV/12 Ranking of generated flowsheet alternatives
Table 5.2: List of knowledge bases developed in the framework
No. Stage/Step Knowledge base Description Appendix
KB2.1 II/3 Translation of unit-operations to task and phenomena
List of different unit operations translated to tasks and PBBs
C.1
KB2.2 II/4 Translation of process hotspots to principle PBBs
A list of alternative tasks and phenomena building blocks (PBBs) based on process hotspots
C.2
KB3.1 III/6 Identification of principle PBBs
A list of principle PBBs identified based on pure and mixture property analysis
C.3
KB3.2 III/11 Translation of basic structures to unit operations
A database guidance to translate basic structures to unit operations
C.4
Page 73
5.2. Algorithms
53
Table 5.3: List of supporting tools used across different steps in the framework
Stage/Tool ProCARPS ProPred Azeopro ASPEN/ PRO/II
ECON SustainPro LCSoft MoT
Stage I * * *
Stage II * * * * *
Stage III
Stage IV * * * * *
5.2. Algorithms
5.2.1. Algorithms: Stage I
Algorithm A1.1: Generation of the binary ratio matrix
This algorithm presents a method to generate the binary ratio matrix. A binary ratio matrix
presents the property differences of each of the binary pairs of components present in the
synthesis analysis as their property ratios except properties like dipole moment where gaseous
species possess zero dipole moment, thus the difference of properties is used instead. Following
steps are followed otherwise to generate the binary ratio matrix.
o A1.1.1. Identify the name and total number of components (NC) in the synthesis problem.
o A1.1.2. Identify the total number of binary pairs using the following equation:
NBP =NC ∗ (NC − 1)
2 (5.1)
NBP – Number of binary pairs and
NC – Number of components
o A1.1.3. Compute binary property ratio and generate the matrix as follows:
- Collect the pure component property data for the list of properties from Table 4.1.
Then compute and store the property ratio for every binary pair as follows:
If,
PAj ≥ PBj (5.2)
Then,
Rij =PAj
PBj (5.3)
Else,
Rij =PBj
PAj (5.4)
Where,
|𝑅𝑖𝑗| > 1 (5.5)
Page 74
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
54
Rij = Binary ratio
PA = Pure component property of component A,
PB = Pure component property of component B
Example: Consider a conceptual example of a mixture with 3 compounds A, B and C. The
objective is to generate binary ratio matrix using algorithm A1.1. A list of 4 pure component
properties for the components is given in Table 5.4. So, applying the algorithm A1.1:
Table 5.4: Pure component properties for the 3 component system
Boiling
point (K) Melting
point (K) Molar volume
(m3/kmol) Molecular
weight (g/mol)
A 231.11 85.47 0.08 44.10
B 272.65 134.86 0.10 58.12
C 309.22 143.42 0.12 72.15
The name and number of components is known (A1.1.1). The number of binary pairs are
calculated to be 3 using equation 5.1 in step A1.1.2. Then, from step A1.1.3, the binary ratio matrix
is generated using equations 5.2 – 5.5 and Table 5.4. The matrix generated is shown in Table 5.5.
Table 5.5: Binary ratio matrix for the 3 component system
Boiling point
(K) Melting
point (K) Molar volume
(m3/kmol) Molecular weight
(g/mol)
A/B 1.18 1.58 1.27 1.32
A/C 1.34 1.68 1.53 1.64
B/C 1.13 1.06 1.20 1.24
5.2.2. Algorithms: Stage II
Algorithm A2.1: Transformation of base case flowsheet to task-based flowsheet
This algorithm presents a method to transform a base case flowsheet (unit-operation scale) to a
task-based flowsheet (task scale). The inlet and outlet in base case flowsheet joining all the unit
operations remains same in task based flowsheet.
o A2.1.1. Classify each unit operation into 3 types of tasks - Mixing, Reaction, Separation
and replace unit operations to generate the task-based flowsheet as follows:
- Reaction task - If in a unit operation, some or all of the inlet components
undergoes the conversion (reaction) to produce new component (s) and has
different inlet and outlet composition, then the unit operation is termed as a
‘reactor’ and is translated as a ‘reaction task’.
Page 75
5.2. Algorithms
55
- Separation task – If in a unit operation, the inlet and outlet compositions are
different and has more than or equal to two outlet streams, then the unit
operation is termed as a ‘separator’ and is translated as a ‘separation task’.
- Mixing task - If in a unit operation, there is no reaction or separation task and
have more than one inlet streams and one or less than the number of inlet streams
in outlet with changed composition, then the unit-operation is termed as a ‘mixer’
and is translated as a ‘mixing task’.
o A2.1.2. A unit operation performing multiple tasks i.e. any combination of above tasks is
also translated. For example, a reactive distillation unit has reaction and separation task
occurring within a single unit, thus the task is defined as reaction-separation task.
o A2.1.3. For a known or identified set of unit operations, the tasks performed can directly
be identified from the knowledge base KB2.1.
Note: The unit operation affecting just change in temperature (for example a plate type heat
exchanger) and pressure (for example pump) are not considered for the task-based flowsheet.
This is because these type of unit operations are added during flowsheet finalization in rigorous
simulation and here algorithm is moving towards lower scale (Babi, 2014). Also, a mixer used for
simulation purposes in process simulators is not considered as a mixing task.
Example: Consider a conceptual example of an equilibrium, liquid phase exothermic reaction
between A and B to produce C and D, followed by the separation of AB from CD using a flash.
Then, AB and CD are separated in two simple distillation columns. The unit-operation based
process flowsheet is given in Figure 5.1. The objective here is to generate a task based flowsheet.
So, applying the algorithm A2.1, all the equipment are first identified in terms of tasks performed
using step A2.1.1. Also, all equipment in the flowsheet are known, thus using step A2.1.2-A2.1.3,
the task based flowsheet is generated as shown in Figure 5.1. Here, reactor is translated to
reaction task while, flash and two distillation columns are translated to separation task.
Algorithm A2.2: Transformation of base case flowsheet to a phenomena-based flowsheet
This algorithm presents a method to transform a base case flowsheet to phenomena based
flowsheet. Here, similar to the task based flowsheet, the inlet and outlet joining all the unit
operations remains same as in base case flowsheet.
o A2.2.1. Retrieve the unit-operation from the unit operations-based flowsheet and tasks
from the task-based flowsheet that are identified using algorithm A1.1
o A2.2.2. Search in the knowledge base KB2.1 for the unit operation retrieved from the base
case and select the list of PBBs.
o A2.2.3. For any unknown unit operations, identify the list of PBBs based on Table 5.6.
Table 5.6 presents the PBBs that can perform an identified task. Further, identify the
phase and class based on the type of task being performed.
Page 76
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
56
o A2.2.4. Replace the tasks in the flowsheet generated in algorithm A1.1 with the PBBs to
generate the phenomena based flowsheet.
Table 5.6: PBBs identification for a task
Task/PBB M 2phM R PC PT PS ES D
Reaction * * * *
Separation * * * * * *
Mixing * * *
Example: Considering conceptual example from algorithm A2.1, the objective is to generate
phenomena based flowsheet. Thus, applying the algorithm A2.2, firstly, the unit operations
retrieved are reactor, flash and 2 distillation column. Here, reactor is performing reaction task
while flash and distillation columns are performing separation task from step A2.2.1. Then in step
A2.2.2, using KB2.1 knowledge base, the list of PBBs are retrieved as follows:
- Reactor (reaction task) ABCD – M, R(L), ES(C)
- Flash (separation task) AC/BD – M,PT(VL), PS(VL)
- Distillation (separation task) A/C – M, 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
- Distillation (separation task) B/D – M, 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
In step A2.2.3, all the tasks in task based flowsheet are replaced with identified PBBs to generate
phenomena based flowsheet (Figure 5.1).
Figure 5.1: Translation of base case flowsheet to task and phenomena based flowsheet
AB M, R(L), ES(C)M, PT(VL),
PS(VL)
M, 2phM, R(L),
ES(C), ES(H),
PC(VL), PT(VL),
PS(VL)
M, 2phM, R(L),
ES(C), ES(H),
PC(VL), PT(VL),
PS(VL)
ABCD
AC
BD
A
C
B
D
Phenomena based
flowsheet
B
D
ABABCD
AC
BD
A
C
Unit operation based
flowsheet
AB Reaction
task
Separation
task
Separation
task
Separation
task
ABCD
AC
BD
A
C
B
D
Task based
flowsheet
Page 77
5.2. Algorithms
57
Algorithm A2.3: Identification of desirable task and phenomena
This algorithm presents a method to identify desirable task and phenomena for an existing
process flowsheet. The primary objective of this algorithm is to identify principle PBBs that can
mitigate the process bottlenecks by expanding the search space. The process hotspots are
translated to the desirable task and phenomena as follows:
o A2.3.1. Using knowledge base KB2.2, select the process hotspot to retrieve corresponding
property binary ratio values and calculate other property values concerning the task.
o A2.3.2. Retrieve additional task and feasible principle PBBs (based on binary ratios using
Appendix C.3) corresponding to the process hotspot and binary pair(s) involved. Also,
screen alternative separation task identified for reaction based on phase feasibility.
o A2.3.3. Add the retrieved principle PBBs to the existing list identified from A2.2 while
making a note that the principle PBBs are not repeated.
Note that, alternative separation task identified for the existing reaction task are for combination
using combinatorial rules (see A3.6) and not as an alternative for the reaction task.
Example: Consider the conceptual example from algorithm A2.1 and 2.2 where one of the
separation task is separation of A and C. Assume that the process hotspot identified here is the
presence of an azeotrope between A and C. The objective here is to identify additional task and
desirable phenomena that could potentially mitigate the process hotspot. Thus, applying the
algorithm A2.3, for the selected process hotspot, the list of property data and binary ratios are
retrieved using step A2.3.1. Assuming, in this case a list of property data to be feasible, the
additional task and corresponding principle PBBs are identified from step A2.3.2 as shown in
Table 5.7. These are then added to an initial list of phenomena using step A2.3.3.
Table 5.7: Additional task and PBBs identified for the process hotspot
Process hotspot
Main task Property/Binary ratio Alternative
task MSA Principle PBBs
Azeotrope Separation
Vapor pressure, solubility parameter
Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
Solubility parameter Separation Y PC(LL), PT(LL), PS(LL)
Vapor pressure, heat of vaporization, boiling point, solubility parameter
Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H), PC(LL), PS(LL)
Vapor pressure, heat of vaporization, boiling point
Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
Molar volume, solubility parameter
Separation N PT(MVL), PS(VL)
Van der Waals volume, critical temp
Separation N PT(MVV), PS(VV)
Solubility parameter, molar volume, radius of gyration
Separation N PT(MLL), PS(LL)
Page 78
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
58
5.2.3. Algorithms: Stage III
Algorithm A3.1: Generation of mathematical combinatorial superstructure of compounds
This algorithm presents a method for generation of a mathematical combinatorial superstructure
of compounds present in the synthesis problem.
o A3.1.1. Identify the reaction task and number of compounds coming out of the reaction
task.
o A3.1.2. Identify the minimum number of separation operations required to separate NC
number of components using equation below:
NST = NC -1 (5.1)
o A3.1.3. Annotate each compound as A, B, C etc.
o A3.1.4. Starting with reaction task, identify sequentially all possible separations of each
compound coming out of the reaction system considering all the possible binary pairs.
Continue this mathematical enumeration for the subsequent remaining separation tasks
i.e. NC-1 tasks for C components to generate the combinatorial superstructure.
Example: Consider a conceptual example of a system that consists of 3 components at the
reactor outlet (A3.1.1). Thus, following step A3.1.2, maximum number of separation tasks required
are 2. From step A3.1.3, the compounds are annotated as A, B and C. The enumeration is done
using step A3.1.4. A mixture of A, B and C can be separated in 6 ways for task 1 separation. The
possibilities for separation task 1 are A/BC, A/CB, B/AC, B/CA, C/AB and C/BA. Further binary
mixture coming out of separation task 1 needs to be separated so the options for A/BC and A/CB
is B/C, for B/AC and B/CA is C/A and for C/AB and C/BA is A/B. The graphical representation of
the superstructure is shown in Figure 5.2.
Figure 5.2: Mathematical combinatorial superstructure for 3 component system
----ABC---- A/BC
A/CB
C/AB
C/BA
B/C
B/AC
B/CA
A/C
A/B
Reaction
task
Separation
task 1
Separation
task 2
Page 79
5.2. Algorithms
59
Note: Equation 5.1 calculates the minimum number of separation tasks required for recovery of
all the compounds present in a system. However, scenarios may arise based on the performance
criteria and objectives of the synthesis problem, where all compounds are not required to be
recovered separately (Babi and Gani, 2014).
Algorithm A3.2: Identification of principle PBBs
This algorithm presents the method to identify feasible principle PBBs for all the binary pairs and
tasks using a knowledge base developed using physical property and thermodynamic insights.
The step at which this algorithm is used consists of only reaction and separation task. Thus,
principle PBBs are identified as follows:
o A3.2.1. Identify principle PBBs for reaction task as follows:
- ‘R’ PBB is always selected for reaction task and thus identify the phase of the
reaction in which reaction is taking place i.e. vapor (V), liquid (L), vapor-liquid
(VL) etc. After identification of phase complete the ‘R’ PBB for example R(V) for
a vapor phase reaction. For multiple phase reaction add ‘2phM’ PBB.
- Identify the type of reaction i.e. exothermic or endothermic to add the energy
supply (ES) PBB completing the list of principle PBBs for a reaction task. It is
identified as follows:
▪ For an exothermic reaction add ‘ES(C)’ PBB and for an endothermic
reaction add ‘ES(H)’ PBB.
▪ For a reaction task taking place in presence of a special energy supply (i.e.
microwave, ultrasound etc.), add ‘ES(D)’ PBB instead of ES(C) or ES(H).
o A3.2.2. Identify principle PBBs for separation task as follows:
- Retrieve the number of binary pairs and all the corresponding pure and mixture
property data from step 1 of the framework in stage I.
- Using the knowledge base KB3.1, select a binary pair to compare the possible
phase condition (mixture or ambient) and binary ratio values of corresponding
component properties. Retrieve and store the principle PBBs that satisfies the
following condition. Alongside note down the separating agent (SA) required.
Rij ≥ Threshold value
- In case of azeotropic (homogeneous and heterogeneous) binary pairs (liquid-
liquid or vapor-liquid) that are identified in step 1 and 2, retrieve and store all the
corresponding principle PBBs. Also, if the mixture analysis shows the binary pair
being pressure sensitive or having a eutectic point, retrieve and store the
corresponding principle PBBs. Alongside note down the separating agent (SA)
required if any.
Page 80
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
60
o A3.2.3. Add and store identified principle PBBs from A2.3 (in case of availability of base
case) to the ones identified in this algorithm and avoid any repetition.
Add ‘*’ sign for a set of principle PBBs requiring any MSA
Example: Consider a conceptual example of a liquid phase exothermic reaction that converts A
to B and C in presence of a heterogeneous catalyst. The reaction is an equilibrium reaction; thus,
outlet of the reactor consists of product B, byproduct C and unreacted A. The objective here is
to identify list of principle PBBs for the reaction and separation tasks. Thus, applying algorithm
A3.2, in step A3.2.1, the phase of the reaction is known alongside the reaction being exothermic
in nature. Thus, for the reaction task the principles PBBs identified are R(L), ES(C). Following
step A3.2.2, number of binary pairs identified are 3 as number of components in the system are
3. Further assuming, a set of binary ratio of pure component properties is shown in Table 5.8.
Table 5.8: Binary ratio matrix for 3 component system
Boiling
point (K) Melting
point (K) Molar volume
(m3/kmol) Vapor
pressure (Pa) Solubility Parameter
(√(kJ/m3))
A/B 1.18 1.58 1.27 1.32 1.08
A/C 1.34 1.68 1.53 1.49 1.12
B/C 1.13 1.06 1.20 1.13 1.04
The binary pair is in liquid phase at both reaction and ambient conditions and does not form any
azeotrope. The binary pair also does not exhibit any miscibility gap and eutectic points. Thus,
using knowledge base KB3.1 and looking at possible feed conditions, the principle PBBs identified
are shown in Table 5.9.
Table 5.9: Identified principle PBBs for different tasks
Task Reaction (A → B)
Separation (A/B) Separation (A/C) Separation (B/C)
Principle
PBBs R(L), ES(C)
PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C)/ES(H) PT(LS), PS(LS), ES(C)/ES(H)
Algorithm A3.3: Generation of phenomena based superstructure
This algorithm presents the method to generate phenomena based superstructure performing
different tasks for the synthesis-intensification problem. The algorithm is as follows:
o A3.3.1. Retrieve mathematical combinatorial based superstructure from step 5 in stage
III. If synthesis problem consists of compounds that are non-condensable, any biomass
in case of bio reactions or solids, then using knowledge based insights fix the task to
separate specific compound and choose relevant sub superstructure.
Page 81
5.2. Algorithms
61
o A3.3.2. Retrieve identified principle PBBs from step 6 in stage III.
o A3.3.3. Place the corresponding principle PBBs against the reaction task and separation
tasks for key binary pair to generate phenomena based superstructure.
o A3.3.4. Add ‘*’ sign for a set of principle PBBs requiring any MSA.
o A3.3.5. Determine the outlet phase for every set of principle PBBs using KB3.1. If multiple
phases are possible then phase from the preceding task is considered as the inlet phase
to the current principle PBB.
o A3.3.6. Remove all the common principle PBBs that are in mathematical alternatives
separating same key compound from the mixture.
Note: This algorithm only generates an initial stage of level 1 phenomena based superstructure.
Level 2 and level 3 phenomena based superstructures are generated using algorithm A3.6.
Example: Consider the conceptual example from algorithm A3.1 and 3.2. Here, the objective is
to generate phenomena based superstructure. Thus, applying the algorithm, firstly, the
mathematical combinatorial superstructure and list of identified principle PBBs are retrieved as
mentioned in steps A3.3.1 and A3.3.2. Then, corresponding principles PBBs are placed for
respective tasks considering key binary pairs (A3.3.3) as shown in Figure 5.3.
Figure 5.3: Phenomena based superstructure generated for example problem
A B + C-----ABC
R(L), ES(C)
A/BC
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
A/CB
B/AC
B/CA
C/AB
C/BA
B/C
A/C
A/B
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
Reaction task Separation task 1 Separation task 2
Page 82
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
62
In Figure 5.3, repetitive PBBs are colored for separation of same compound from the considered
mixture. As no set of principle PBB requires any MSA as identified in algorithm A3.2, thus step
A3.3.4 is skipped. Further, as mentioned in step A3.3.5, the possible outlet phase for all the set of
principle PBBs is identified using KB3.1 and repetitive PBBs are removed as mentioned in step
A3.3.6. An updated phenomena based superstructure is then shown in Figure 5.4.
Figure 5.4: Updated phenomena based superstructure generated for example problem
Algorithm A3.4: Reduction of alternatives
This algorithm presents the method for reduction of phenomena based superstructure generated
in step 8. This algorithm is divided into two sections i.e. reduction using feasibility rules and
logical rules. The algorithm is presented as follows:
• Feasibility Rules
Level 1 - Task based feasibility rules
o A3.4.1. Retrieve outlet phase of the reaction from the mixture analysis in step 1.
o A3.4.2. If the reaction mixture consists of solids in the system the first separation task
after reaction should be removal of solids and thus remove all other alternatives from
the first task after the reaction.
o A3.4.3. If the reaction mixture consists of vapor-liquid, the phases need to be
separated first after removing the solids and thus, other subsequent alternatives are
removed.
A B + C-----ABC
R(L), ES(C)
A/BC
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
B/AC
C/AB
B/C
A/C
A/B
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
Reaction task Separation task 1 Separation task 2
L V-LV-L
L-S
V-LV-L
L-S
V-LV-L
L-S
Page 83
5.2. Algorithms
63
o A3.4.4. If the mixture consists of non-condensable gases, then non-condensable
needed to be removed first thus, removing all other subsequent alternatives.
Level 2 - Phenomena based feasibility rules
o A3.4.5. If there is no azeotrope present for a binary pair and identified set of principle
PBBs include PT(VL) with no added separating agent, then the alternatives separation
not in order of boiling point of compounds are eliminated.
o A3.4.6. Eliminate the set of identified principle PBBs with PT(LS) and no added
separating agent, if the separation task is not in order of melting point of compounds.
• Logical Rules
Level 3 – Conditional rules
o A3.4.7. Retrieve the phenomena based superstructure from step 9 and identify
feasible inlet feed conditions for all the principle PBBs.
o A3.4.8. Remove principle PBBs consisting of phenomena mentioned in Table 5.10
that are not falling within the temperature range and phases of ambient mixture
conditions or feed conditions. Also, in case of presence of azeotrope, eutectic mixture
or difficult separating mixture for the considered binary pair, add required energy
supply PBBs from Table 5.10.
Table 5.10: Logical set of conditions for different transition PBBs
PBB Feed
conditions
Additional
Phenomena*
Operating
temperature
PT(MVV) V - -
PT(MVV) L, VL ES(H)/ES(D) -
PT(MLL) L - -
PT(MLL) V, VL ES(C) >0 ˚C
PT(MVL) L - -
PT(MVL) V, VL ES(C) -
PT(LS) L ES(D) >0 ˚C
PT(VL) V, L, VL ES(D) -
PT(LL) L - -
PT(VS) V, S, VS ES(C)/ES(H)/ES(D) -
o A3.4.9. After all reductions, update phenomena based superstructure from step 9.
Example: Consider phenomena based superstructure generated in conceptual example from
algorithm A3.3 (Figure 5.4). The objective here is to apply reduction rules from algorithm A3.4.
Algorithm is explained with examples at three different levels.
Page 84
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
64
• Level - 1
Consider same superstructure in Figure 5.4 with reactor outlet conditions as V-L. Here,
component C is in vapor phase and is non condensable while component A and B are in
liquid phase. Thus, following steps A3.4.1-A3.4.4, the first task is removal of solids i.e.
removal of C from A and B. Thus, in same superstructure, except C/AB or C/BA all other
task in separation task 1 are removed. An updated superstructure is shown in Figure 5.5.
Figure 5.5: Phenomena based superstructure generated after level 1 reduction
• Level - 2
Consider Figure 5.4 with order of boiling and melting point for components as A>B>C
and no azeotrope. Thus, following step A3.4.5-A3.4.6, separation of B from A and C using
PT(VL) and PT(LS) is infeasible. So, alternatives in separation task 1 with PBB ‘PT(VL)’
and ‘PT(LS)’ are removed that contains separation of B/AC. An updated superstructure is
shown in Figure 5.6.
Figure 5.6: Phenomena based superstructure generated after level 2 reduction
A B + C-----ABC
R(L), ES(C)
C/AB A/B
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
Reaction task Separation task 1 Separation task 2
V-L V-LV-L
L-S
A B + C-----ABC
R(L), ES(C)
A/BC
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
B/AC
C/AB
B/C
A/C
A/B
PT(MVL), PS(VL)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
Reaction task Separation task 1 Separation task 2
L V-LV-L
L-S
V-L
V-LV-L
L-S
Page 85
5.2. Algorithms
65
• Level - 3
Consider Figure 5.5, where the outlet of the reaction task is V-L with presence of a non-
condensable. Thus, applying step A3.4.7, the phenomena based superstructure is
retrieved along with feed conditions. These are then checked (A3.4.8) upon with Table
5.10, where in absence of any azeotropic or eutectic mixture, it is identified that the
phases allowed for principle PBB with phenomena ‘PT(MVL)’ and ‘PT(LS)’ is L, while for
‘PT(VL)’ is V, L or VL. Thus, according to reaction task outlet phase which VL, only
principle PBB with phenomena ‘PT(VL)’ is logical. The updated superstructure (A3.4.9)
after this reduction is shown in Figure 5.7.
Figure 5.7: Phenomena based superstructure generated after level 3 reduction
Algorithm A3.5: Transformation of principle PBBs to basic structures
This algorithm presents the method for translating principle PBBs to basic structures by selecting
SPBs from step 7 that can perform desired task.
o A3.5.1. Identify the task activity for set of principle PBBs i.e. reaction, separation.
• Reaction
o A3.5.2. For reaction task, look for reaction PBBs within the set of principle PBBs that
need to be translated to basic structure.
o A3.5.3. Select SPBs from feasible list of SPBs generated in step 7 consisting of reaction
PBB without any mass transfer PBB.
o A3.5.4. Screen those selected set of SPBs based on the mixing and energy supply PBBs
present in principle PBBs. In case of presence of multiple energy supply PBBs, identify
additional SPB consisting of only special energy supply PBB.
o A3.5.5. Combine screened SPBs if multiple SPBs are available for basic structure.
• Separation
o A3.5.6. For separation task, look for the mass transfer PBBs within the set of principle
PBBs that need to be translated to basic structure. Then, perform steps A3.5.7-A3.5.9
for same phase PBBs in a single SPB.
A B + C-----ABC
R(L), ES(C)
C/AB A/B
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
Reaction task Separation task 1 Separation task 2
V-LV-L
Page 86
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
66
o A3.5.7. Select SPBs from feasible list of SPBs generated in step 7 consisting of all mass
transfer SPBs from the considered set of principle PBBs without reaction PBBs.
o A3.5.8. Screen those selected set of SPBs based on the energy supply SPBs present in
principle PBBs and possible inlet feed conditions.
o A3.5.9. Combine screened SPBs if multiple SPBs are available to form a basic structure
in a way that energy supply PBBs are always separated by a non-energy transfer SPB
except those with direct energy transfer PBBs if present.
o A3.5.10. Replace principle PBBs with identified basic structures in phenomena based
superstructure from step 8.
o A3.5.11. In presence of MSA and its separation, select SPBs consisting of principle
PBBs – “PT(MLL), PS(LL)”, “PT(MVL), PS(VL)”, “PT(MVV), PS(VV)” and “PC(VL),
PT(VL), PS(L), ES(C), ES(H)” to generate basic structures by following A3.5.7-A3.5.9.
Example: Consider a list of feasible SPBs shown in Table 5.11, generated from list of PBBs. The
objective here is to generate basic structures for principle PBBs from superstructure in Figure
5.7. Thus, applying the algorithm first for reaction task. The reaction PBB within principle PBBs
is R(L), thus SPB 3, 6, 7, 8, 11 and 12. These SPBs are screened in step A3.5.3, as the principle PBBs
consists of ES(C) PBB without any 2 phase mixing taking place. Thus, only SPB left after screening
is SPB no. 7. For separation task, there are 3 sets of principle PBBs. The translation is performed
individually for all. The first set of principle PBBs is 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H).
So, from step A3.5.7, SPB number 23, 24 and 25 are selected. Then screening selected SPBs based
on A3.5.8, SPB 24 and 25 are considered for combination in A3.5.9. As, SPB 24 and 25 consist of
energy supply PBBs, they need to be separated with non-energy supply SPB with same set of mass
transfer PBBs. Required SPB is identified to be SPB 23, which is then placed in between SPB 24
and 25 to generate the required basic structure. Similarly, for second and third set of principle
PBBs, SPB 29 and SPB 31 are identified individually to become required basic structures. Here,
SPB 31 is selected instead of SPB 32, because of incoming feed which is liquid, thus transition will
take place by cooling instead of heating as both A and B are liquid at ambient conditions.
Figure 5.8: Phenomena based superstructure with basic structures (Level 1 superstructure)
A B + C-----ABC C/AB A/B
Reaction task Separation task 1 Separation task 2
V-LV-L
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C)
M=R(L)=ES(C)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
Page 87
5.2. Algorithms
67
Table 5.11: Example list of feasible SPBs to generate basic structures in algorithm A3.5
SPB Connected PBB Task they may perform
SPB.1 M Mixing
SPB.2 M=2phM Mixing
SPB.3 M=R(V) Mixing+Reaction
SPB.4 M=ES(H) Mixing+Heating
SPB.5 M=ES(C) Mixing+Cooling
SPB.6 M=R(V)=ES(H) Mixing+Reaction+Heating
SPB.7 M=R(V)=ES(C) Mixing+Reaction+Cooling
SPB.8 M=2phM=R(V) Mixing+Reaction
SPB.9 M=2phM=ES(C) Mixing+Cooling
SPB.10 M=2phM=ES(H) Mixing+Heating
SPB.11 M=2phM=R(V)=ES(C) Mixing+Reaction+Cooling
SPB.12 M=2phM=R(V)=ES(H) Mixing+Reaction+Heating
SPB.13 M=2phM=PC(VL)=PT(VL) Mixing+Phase creation
SPB.14 M=2phM=R(V)=PC(VL)=PT(VL) Mixing+Reaction+ Phase creation
SPB.15 M= 2phM= ES(C)=PC(VL)=PT(VL) Mixing+Cooling+ Phase creation
SPB.16 M= 2phM= ES(H)=PC(VL)=PT(VL) Mixing+Heating+ Phase creation
SPB.17 M=2phM =R(V)=ES(C) =PC(VL)=PT(VL) Mixing+Reaction+Cooling+Phase creation
SPB.18 M=2phM=R(V)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+Phase creation
SPB.19 M=PT(VL)=PS(VL) Mixing+Separation
SPB.20 M=ES(C)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.21 M=ES(H)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.22 M=R(V)=ES(H)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.23 M=2phM=PC(VL)=PT(VL)=PS(VL) Mixing+Separation
SPB.24 M=2phM=ES(H)= PC(VL)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.25 M=2phM=ES(C) =PC(VL)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.26 M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Separation
SPB.27 M=2phM =R(V)=ES(H) =PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.28 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation
SPB.29 M=PT(MVL)=PS(VL) Mixing+Heating+Separation
SPB.30 M=PT(LS)=PS(LS) Mixing+Separation
SPB.31 M=ES(C)=PT(LS)=PS(LS) Mixing+Cooling+Separation
SPB.32 M=ES(H)=PT(LS)=PS(LS) Mixing+Heating+Separation
SPB.33 D Stream division
Page 88
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
68
Among identified basic structures, SPB 7 and SPB 31 can also be represented as combination of
SPB 3 and 5 for reaction task and SPB 5 and 30 for separation task respectively. The updated
superstructure with all identified basic structures is shown in Figure 5.8.
Algorithm A3.6: Generation of alternatives by combining basic structures
This algorithm presents the method for combining the basic structures that can perform multiple
tasks. Here, two level (2 and 3) of phenomena based superstructures are generated. At level 2
two adjacent task are combined from level 1, while at level 3 two adjacent task are combined form
level 2. The basic structures can be combined using following rules:
o A3.6.1. Adjacent reaction and separation task can be combined to generate a basic
structure with reaction-separation task occurring in one structure with following rule.
- The phase of the key binary pair coming out of the reactor should be same as the
phase of inlet of the adjacent separation task.
- The reaction-separation task in a single basic structure can have a maximum of 4
outlets (an example being Kaibel column by Lopez-Saucedo et al. (2018)).
o A3.6.2. Adjacent separation tasks sharing the same basic structure with ‘PT(VL)’,
‘PT(VS/LS)*’ as one of the principle PBB can be combined to generate a structure
performing multiple tasks.
- The combined basic structure with ‘PT(VL)’ PBB can have a maximum of 4 outlets
(an example being Kaibel column by Lopez-Saucedo et al. (2018)).
o A3.6.3. If, a basic structure of one of an adjacent task consist one of the following
phenomena:
PT(MVL), PT(MVV), PT(MLL)
Then the following combinations rules are applied:
- The basic structure that consists of ‘R’ PBB and same phase for the key binary pair,
can be combined to generate a new basic structure.
- The combined basic structure with ‘R’ PBB should not remove any of the reactant.
- Above phenomena cannot be combined with each other in adjacent tasks.
o A3.6.4. The principle PBBs that use MSA may or may not (fixed MSA) require additional
separation task and thus any additional task required can only be combined with the
adjacent reaction task.
o A3.6.5. Adjacent basic structures with SPB having ES(C) phenomena along with PT(LS)
cannot be combined with structure having SPB with ES(H) and/or PT(MVV).
o A3.6.6. The last separation task of a binary pair with basic structure having principle SPB
PT(VL) can only be combined with similar SPB consisting of vapor-liquid phenomena.
o A3.6.7. A basic structure with principle PBBs ‘PT(VL), PS(VL)’ can only be combined with
adjacent following basic structure but not preceding one along with phase feasibility.
Page 89
5.2. Algorithms
69
Example: Consider, the level 1 superstructure shown in Figure 5.8. The objective here is to
combine basic structures to generate level 2 and level 3 phenomena based superstructures. Thus,
first applying the algorithm to generate level 2 superstructure. According to step A3.6.1, adjacent
reaction-separation task can be combined. So, following combination rules, the adjacent tasks
are combined to generate a new basic structure performing reaction and separation task
together. Similarly, adjacent separation tasks are combined using step A3.6.2-A3.6.7. The basic
structure at separation task 1 can be combined with all the basic structures in separation task 2
except one with principle PBBs of ‘PT(LS), ES(C)’ according to step A3.6.5. Thus the new basic
structures generated at level 2 is shown in Figure 5.9.
Figure 5.9: Level 2 (a, b) and level 3 phenomena based superstructure
A B + C
--ABC--C/AB--A/B
Reaction-Separation task 1 Separation task 2
V-L
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(L)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
C/AB - A/B
Separation - Separation
task (1 and 2)
A B + C-----ABC
Reaction task
V-LM=R(L)=ES(C)M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
Level 2a
Level 2b
A B + C
--ABC--C/AB—A/B
Reaction-Separation-
Separation task
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=2phM=R(L)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(L)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
Level 3
Page 90
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
70
Level 3 superstructure is generated by using level 2a and 2b superstructures. Thus, again using
combinatorial algorithm steps, the combined basic structures at level 3 is shown in Figure 5.9.
Algorithm A3.7: Translation of basic structures to unit-ops
This algorithm presents the method to translate basic structures to unit-operations generating
process flowsheet alternatives at unit-operation level.
o A3.7.1. Identify the SPBs building block including reaction or mass transfer PBBs within
the key basic structure that consist one or more than one SPBs.
o A3.7.2. Using the knowledgebase KB3.2, select the SPBs and identify the associated unit
operation.
o A3.7.3. If a basic structure does not match any of the listed equipment then potentially a
novel equipment is generated.
o A3.7.4. Replace every basic structure with the identified unit operation and generate
flowsheet alternatives while screening them using feed phase, use of mass or energy
separating agent and number of possible outlets.
Note: The basic structures, involving membrane operations as a first unit operation involving
separations are not translated to flowsheet alternatives except binary pair with azeotropes or
difficult separations.
Example: Consider the superstructures shown in Figure 5.8 and 5.9, where the objective is to
translate the basic structures to unit-operations generating process flowsheet alternatives at
unit-operation level. Applying algorithm A3.7, a reaction, separation and reaction-separation
basic structure is translated as follows:
- Conceptual example for reaction basic structure: The SPB for reaction task in level 1
superstructure (A3.7.1) with building block SPB is M=R=. Further, looking into knowledge
base, the unit operation identified (A3.7.2) based on SPB are shown in Table 5.12.
Table 5.12: Unit-operations based on basic structure for reaction
SPB building
block Task Unit-operation
Screening 1 Feed/Reaction
Phase
Screening 2 MSA Y/N
Screening 3 Azeotrope
Screening 4 Min no. of
outlets
M=R= Reaction Batch reactor S, V and/or L Y/N - 1
M=R= Reaction Semi-batch reactor S, V and/or L Y/N - 1
M=R= Reaction CSTR L Y/N - 1
M=R= Reaction Tubular Reactor
(PFR) V N - 1
M=R= Reaction Pack-bed reactor S and/or V N - 1
Further, the alternatives identified are screened based on reaction phase (A3.7.3) where
most suitable operation identified is a CSTR (continuous stir tank reactor).
Page 91
5.2. Algorithms
71
- Conceptual example for separation basic structure: The SPB identified for separation
task 1 (A3.7.1) in level 1 with building block SPB is =2phM=PC(VL)=PT(VL)=PS(VL).
Further, looking into knowledge base, the unit operation identified (A3.7.2) based on SPB
are shown in Table 5.13.
Table 5.13: Unit-operations based on basic structure for separation
SPB building block Task Unit-
operation
Screening 1
Feed phase
Screening 2
MSA Y/N
Screening 3
Azeotrope
Screening 4
Min no. of outlets
=2phM=PC(VL)=PT(VL)=PS(VL) Separation Distillation V and/or L N Y/N 2
=2phM=PC(VL)=PT(VL)=PS(VL) Separation Kaibel
Column V and/or L Y/N Y/N 4
=2phM=PC(VL)=PT(VL)=PS(VL) Separation Dividing Wall
Column V and/or L N N 3
Further, screening based on number of outlets distillation alternative is identified as the
potential unit operation.
- Conceptual example for reaction-separation basic structure: The SPBs identified for
one of the reaction-separation task (A3.7.1) in level 3 consists of two key SPB building
blocks. These are ‘=2phM=R=PC(VL)=PT(VL)=PS(VL)’ and ‘=PT(MVL)=PS(VL)’. Further,
looking into knowledge base, the unit operation identified (A3.7.2) based on SPBs is
shown in Table 5.14.
Table 5.14: Unit-operations based on basic structure for reaction-separation
SPB building block Task Unit-operation
Screening 1
Feed phase
Screening 2
MSA Y/N
Screening 3
Azeotrope
Screening 4
Number of outlets
=2phM=R=PC(VL)=PT(VL)=PS(VL), =PT(MVL)=PS(VL)
Reaction - Separation
Membrane reactive
distillation column
V and/or L N Y/N 3
Similarly, for all other basic structures, unit-operation are identified to generate unit-operation
based flowsheet alternatives (A3.7.3-A3.7.4). An example of flowsheet alternatives generated at
each level is shown in Table 5.15.
Table 5.15: Unit-operation based flowsheet alternatives
Level Flowsheet alternative
3 Reactive divided wall distillation
2 Reactive distillation → VP membrane
1 Reaction →Distillation → Distillation
Page 92
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
72
5.2.4. Algorithm: Stage IV
Algorithm A4.1: Ranking of feasible flowsheet alternatives
This algorithm presents the method to rank the flowsheet alternatives generated in stage III. The
objective of this algorithm is to calculate the Enthalpy Index (EI) for all the feasible flowsheet
alternatives in order to rank them to identify potential alternatives for detailed analysis.
o A4.1.1. Calculate enthalpy for individual unit-operations in all the feasible flowsheet
alternatives as follows:
- For a reactor, retrieve the enthalpy of the reaction from step 2.
- For other unit operation, perform mass balance across unit-operations using simple
mass balance models like mixer, splitter and separator (Appendix D.1) by identifying
the recovery factors (Appendix D.2-indicative list) (Tula, 2016).
- Identify inlet-outlet conditions across the unit-operation using process information
(Appendix D.2-indicative list) (Tula, 2016).
- Retrieve heat capacity data for inlet and outlet process streams.
- Calculate enthalpy change (outlet subtracted from inlet streams) for all the unit
operation using mass balance, temperature and heat capacity data across the streams.
o A4.1.2. Calculate overall enthalpy of a process alternative by adding individual enthalpies
of unit operations involved.
o A4.1.3. Calculate the Enthalpy Index (EI) for all the alternatives using following equation:
EI𝑘 =|∆H|lowest
|∆H|𝑘
(5.2)
o A4.1.4. Rank the alternatives at different levels with highest Enthalpy Index (EI) being
the top ranked alternative.
Example: Consider the flowsheet alternatives generated at the different levels (Table 5.15) in
conceptual example from A3.6. The objective here is to rank the flowsheet alternatives by
calculating enthalpy index (EI). Thus, applying algorithm A4.1 to flowsheet alternative generated
at level 1 in Table 5.14. In step A4.1.1, assume enthalpy of the reaction is -35 kJ/mol and for a
distillation column the mass balance is performed by taking recovery of the components lighter
than the light key is equal to 100% in the overhead product and the recovery of the components
heavier than the heavy key is equal to 100% in the bottom product. The recovery of the key
components is greater than or equal to 99.5%. The distillate temperature is set at bubble point
or, in case of non-condensable, dew point. The bottoms stream of the distillation process-group
is always set at bubble point. Thus, retrieving the specific heat capacity data, the enthalpy change
is calculated. Assume, enthalpy calculated for two distillation column in considered flowsheet
alternative is -28 kJ/mol and -11 kJ/mol. Thus, overall enthalpy is calculated by adding enthalpy
Page 93
5.3. Knowledge bases
73
of 3 unit operations which comes out to be -74 kJ/mol. Similarly, consider the overall enthalpy
of other flowsheet alternative at level 2 and level 3 in Table 5.14 to be -39 kJ/mol and -59 kJ/mol
respectively. The EI is calculated for 3 alternatives using equation 5.2 and are ranked as shown
in Table 5.16.
Table 5.16: Ranking of flowsheet alternatives for a conceptual example using A4.1
Level Flowsheet alternative Enthalpy Index (EI) Rank
2 Reactive distillation → VP membrane 1.00 1
3 Reactive divided wall distillation 0.66 2
1 Reaction →Distillation → Distillation 0.53 3
5.3. Knowledge bases
There are 4 knowledge bases that are developed fir phenomena-based synthesis intensification
framework. An overview of all the knowledge bases is given in Table 5.2.
• Knowledge base KB2.1: Translation of unit-operation to task and phenomena This knowledge base is developed (Appendix C.1) to translate existing process flowsheet
to lower scale i.e. task and phenomena scale, thus generating task and phenomena based
flowsheet. This knowledge base assists to access an initial search space in which existing
process flowsheet is built. It mainly consists of known unit-operations found in literature
that can perform the reaction, separation, reaction-separation, and separation-separation
task. The knowledge base along with task and phenomena associated with the unit-
operation provides information about the possible feed/reaction phase, any separating
agent required, type of separating agent and any phase being added or created within the
unit operation. The knowledge is primarily used in step 3 in stage II of the framework.
• Knowledge base KB2.2: Translation of process hotspots to principle PBBs This knowledge base is developed (Appendix C.2) to translate the process hotspots
identified in the base case to additional task and desirable phenomena that may assist in
mitigating them. This knowledge base assists to expand the initial search space for an
existing process flowsheet, thus providing opportunities to generate novel solutions. The
knowledge base consists of different process hotpots, the task process hotspot associated
to, an alternative task that may be performed to mitigate the hotspot, possible list of
property analysis required to verify alternative task, use of mass separating agent and list
of phenomena associated with the alternative task. The process hotspot database is based
on detailed analysis in terms of economics, sustainability and life cycle assessment. The
knowledge base is primarily used in step 4 in stage II of the framework.
Page 94
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
74
• Knowledge base KB3.1: Identification of principle PBBs This knowledge base is developed (Appendix C.3) to identify the list of principle PBBs for
every binary pair present in the synthesis-intensification problem. This knowledge base
is the fundamental pillar of the framework as it provides the complete search space in
terms of phenomena that may assist in achieving the desired task while generating novel
and innovative solutions. It is developed based on physical property and thermodynamic
insights from Jaksland et al. (1995). The properties and thermodynamic insights provide
information about potential driving force behind the task. For example, a significant
difference in melting point of a binary pair drives separation task by transition of one of
the components from liquid to solid phase. For an exothermic reaction task, the task can
be driven by continuously removing heat, thus exploiting the energy supply phenomena.
The knowledge base consists of physical and thermodynamic properties, its threshold
values above which a set of principle PBBs are selected for a feasible phase, potential
outlet phase and any MSA that may be required along with the set of principle PBBs. The
knowledge base thus developed is used in step 6 of stage II.
• Knowledge base KB3.2: Translation of basic structure to unit-operations This knowledge base is developed (Appendix C.4) to translate the basic structures of
phenomena to unit-operations, thus generating unit-operation based process flowsheet
alternatives. The knowledge base consists of SPB building block to be identified based on
the basic structure, task performed by the basic structure and unit-operation. Further,
there are different screening criteria based on feasible phase, mass separating agent,
presence of azeotrope and possible number of outlets from the task. The knowledge base
is used in step 11 of stage III.
5.4. Supporting tools
Over the course of four stages, there are different tools that are used being shared by all or some
of the stages. An overview of usage of different supporting tools at different stages is given in
Table 5.3. These are described in different sections as follows:
• Modelling and simulation tools Modelling and simulation tools are used in stage II and stage IV of the framework.
Modeling tool ICAS-MoT (Fedorova et al., 2014) is used which is also a part of ICAS (Gani,
2002). There are other similar tools like GAMS (GAMS Development Corporation, 2012),
gPROMS (Barton et al., 1993) that can also be used to perform modelling. While for
simulation primarily PRO/IITM/Aspen PlusTM is used, whereas tools like CHEMCADTM
can also be used for the same purpose. These simulation tools contain detailed property
models, model equations and calculation tools for standard unit-operations that can be
directly used while in modelling tools, these can be generated to fulfil the purpose of a
Page 95
5.5. Chapter summary
75
specific unit-operation. The primary objective of these tools is to generate detailed mass
and energy balance along with design data.
• Analysis tools Analysis tools are used in stage II and stage IV to analyze the process flowsheets in terms
of economics, sustainability and life cycle assessment. ECON (Saengwirun, 2011) tool is
used to perform economic analysis. In this tool, similar to some other economic analysis
tools, the economic parameters are calculated via the Guthrie Method (Seider et al.,
2008). These economic parameters include operating costs (OPEX) including utility
costs, capital costs, return on investment and production costs. SustainPro (Carvalho et
al., 2013) tool is used to perform sustainability analysis where factors such as energy and
waste cost (EWC), material value added (MVA) and total value added (TVA) are
calculated to determine the process hotspots specifically in stage II. LCSoft (Kalakul et
al., 2014) is a tool used in stage II and IV to perform life cycle analysis and thus obtain
sustainability indicators in terms of global warming potential (GWP), carbon footprint,
human toxicity (HTPI, HTPE) to name a few.
• Other tools There are some other tools for example ProCARPS (Cignitti, 2014), ProPred, Azeopro that
may be used to carry out specific tasks. In case of missing properties for certain
compounds, ProPred can be used to calculate them. ProPred and Azeopro are also part
of ICAS software (Gani et al. 1997; Gani 2002). ProCARPS can be used to identify possible
reaction paths producing desired products from certain raw materials. Azeopro is used
to identify potential azeotropes in the synthesis analysis which is also a part of ICAS
software. ICAS database (Gani et al. 1997; Gani 2002) is also used at different steps of
framework to retrieve property data.
5.5. Chapter summary
The algorithms that are used while performing phenomena-based synthesis intensification along
with knowledge bases and associated tools were presented. Algorithms operates at phenomena,
task and unit operation level that creates an entirely new search space generating novel solutions.
The knowledge base assists phenomena based synthesis method to operate at all possible phases
covering VLE, SLE and LLE; thus, allowing to generate multiple solutions for a single synthesis
problem. Finally, an overview of supporting tools was also given.
Page 96
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
76
Page 97
5.5. Chapter summary
77
PART - III
The third part of thesis presents the application of the developed
phenomena-based synthesis-intensification framework. The 4-
stage framework is applied to the three different case studies
including chemical and biochemical production processes. The
case studies includes direct and indirect synthesis application of
the framework. The first case study is the production of a
chemical considered as a green energy source, Dimethyl Ether
(DME) as a direct synthesis problem. The second case study is the
Hydrodealkylation (HDA) of toluene to produce benzene as a
primary product. In this case, indirect synthesis is used to
generate more innovative, sustainable and economic solutions
than an existing process flowsheet. The third case study is a bio
process where biological production of the succinic acid is
considered. In this case, first an optimal base case is synthesized
using superstructure-based optimization approach. The base
case is then designed and analysed in detail to identify potential
improvements. Then, PBS-intensification framework is applied
by selecting the optimal base case to solve an indirect synthesis-
intensification problem.
Page 98
PBS-Intensification: Algorithms, Knowledge bases and Supporting tools
78
Page 99
5.5. Chapter summary
79
Chapter 6 Case Studies
In this chapter, three example case studies are presented, highlighting each step of
the phenomena-based synthesis-intensification framework. These case studies
are: Production of Dimethyl Ether (DME), Hydrodealkylation (HDA) of toluene,
Production of bio-succinic acid. In case study 1 and 2, the developed framework
for phenomena-based synthesis-intensification is applied which is followed by the
discussion about the results obtained. In third case study, the base case is first
synthesised by identifying an optimal processing route. The optimal process is
then designed, analysed for the process hotspots and intensified using indirect
phenomena-based synthesis-intensification method. The results generated are
then discussed and compared to the base case.
Chapter outline:
6.1. Production of Dimethyl Ether (DME)
6.1.1. Framework application
6.1.2. Discussion
6.2. Hydrodealkylation (HDA) of Toluene
6.2.1. Framework application
6.2.2. Discussion
6.3. Production of Bio-Succinic Acid
6.3.1. Synthesis and design using superstructure based optimization
6.3.2. Application of extended phenomena-based synthesis method
6.3.3. Framework application
6.3.4. Discussion
6.4. Chapter summary
These journal articles are partially based on this chapter:
Garg, N., Kontogeorgis, G.M., Gani, R. and Woodley, J.M., 2019, “A process synthesis-
intensification method for generation of novel and intensified solutions”, in preparation.
Garg, N., Woodley, J.M., Gani, R. and Kontogeorgis, G.M., 2019, “Sustainable solutions
by integrating process synthesis-intensification”, Computers and Chemical Engineering,
126, 499-519.
Page 100
Case Studies
80
6.1. Case study 1: Production of Dimethyl Ether (DME)
DME is categorized as a green energy source and the demand for DME continues to increase as
it is expected to reach 11.72 billion USD by 2023 (report by Crystal Market research, 2017). It is
also a non-toxic, well-known propellant, coolant and a clean burning fuel for diesel engines. DME
as a fuel also provides high performance and low emission of greenhouse gases like CO, NOx and
particulates in its combustion as compared to other energy sources. This makes DME a preferable
source of energy over many of the others (Figure 6.1). The major producers of DME are Korea
Gas corporation, Guangdong JOVO Group CO ltd., Royal Dutch Shell, Toyota Tsusho, Mitsubishi
Corporation to name a few (Egypt Business Directory, 2018).
Figure 6.1: Importance of DME (with permission-Volvo Sustainability report, 2013)
Objective of the case study: To identify novel, innovative and intensified flowsheet alternatives
for the production of DME from methanol as a raw material with a purity of at least 99.8 mol %
(fuel grade).
6.1.1. Framework application
Stage I: Synthesis analysis
• Step 1: Problem definition
The synthesis problem definition is to produce DME from methanol with a purity of at
least 99.8 mol % (fuel grade) which is a design constraint and performance criteria for
this problem. A joint venture has been established by 9 different companies in Japan to
produce 80 kt/y of DME (http://japan-dme.or.jp/english/dme/production.html) with
the potential expansion to 100kt/y, thus for this case the target annual production of
DME has been set to 100 kt/y.
- S1.1. Problem type
The problem type identified is direct synthesis as no prior information about process
flowsheet is selected to produce DME of required specifications from methanol.
Page 101
6.1. Case study 1: Production of Dimethyl Ether (DME)
81
- S1.2. Information collection
DME in industry is generally produced from two kinds of processes: Indirect method
via dehydration of methanol (MeOH) and direct method where DME is synthesized
from synthesis gas. Most of the industrial DME is currently produced by indirect
method (Japan DME Association). The reaction pathway identified by performing
literature search is shown below.
2CH3OH ⇌ CH3OCH3 + H2O
The methanol dehydrates in the presence of Al2O3 catalyst to produce DME and water
(Zhang et al., 2011). The reaction is an equilibrium reaction and operates at 593.15 K
and 0.1 MPa pressure. Being an equilibrium reaction, the outlet of the reactor consists
of DME, water and unreacted methanol.
• Step 2: Problem analysis
In this step all the necessary reaction, physical property and thermodynamic analysis is
performed which is required for rest of the stages. This is carried out in terms of reaction
analysis and mixture analysis.
- S2.1. Reaction analysis
The reaction in step 1 confirms the possibility to produce DME from methanol. The
reaction takes place at high temperature in vapor phase. The equilibrium conversion
of the reaction is 84.38% (Zhang et al., 2011). The catalyst used is a heterogeneous
catalyst. The reaction is reversible and thus, kinetic data for the reaction is retrieved
from Zhang et al. (2011). The heat of reaction is -23.5 kJ/mol, which makes reaction
to be exothermic as it is less than zero.
- S2.2. Mixture analysis
The outlet of the reactor consists of DME, water and unreacted methanol. In this part
of step 2, the pure and mixture component analysis is performed to set up the basis
for stage III.
Pure component analysis
The list of pure component properties is retrieved from ICAS database (Gani et
al. 1997; Gani 2002) and literature search. The retrieved list is shown in Table 6.1.
Then, by following the steps A1.1.1-A1.1.2 of algorithm A1.1, the number of binary
pairs are calculated to be 3 as the number of compounds in the problem are
identified to be 3 (Methanol (MeOH), DME and Water). These components are
annotated as A, B and C respectively. Then, the binary ratio matrix of pure
component properties for binary pairs is calculated using step A1.1.3 of algorithm
A1.1. The binary ratio matrix for a selected set of pure component properties is
shown in Table 6.2.
Page 102
Case Studies
82
Table 6.1: Pure component properties data for the compounds involved in the problem
Property UOM MeOH (A) DME (B) Water (C)
MW (g/mol) 32.04 46.07 18.02
ω - 0.56 0.20 0.34
Tc (K) 512.64 400.10 647.13
Pc (bar) 79.91 53.00 217.67
Zc - 0.22 0.27 0.23
Vc (m3/kmol) 0.12 0.17 0.06
Tb (K) 337.85 248.31 373.15
dm (Debye) 1.70 1.30 1.85
rg (Å) 1.55 2.15 0.62
Tm (K) 175.47 131.66 273.15
Ttp (K) 175.47 131.65 273.16
Ptp (Pa) 0.11 3.01 603.73
MV (m3/kmol) 0.01 0.07 0.02
Hf (kJ/kmol) -200940 -184100 -241810
Gf (kJ/kmol) -162320 -112800 -228590
SIG (kJ/kmol·K) 239.88 266.70 188.72
Hfus (kJ/kmol) 3215.00 4937.00 6001.70
Hcomb (kJ/kmol) -638200 -1328400 0.00
δ (√(kJ/m3) 29.59 15.12 47.81
Vvw (m3/kmol) 0.02 0.03 0.01
Avw (m2/kmol) 3.58E+08 4.84E+08 2.26E+08
Pvap (Pa) 16832.70 637841.0 3170.00
log Kow - -0.77 0.10 -1.38
Hvap (kJ/mol) 35.20 21.50 40.70
d (pm) 376 465 296
Page 103
6.1. Case study 1: Production of Dimethyl Ether (DME)
83
Table 6.2: Binary ratio matrix for the selected set of properties
Property MeOH/DME
(A/B) MeOH/Water
(A/C) DME/Water
(B/C)
MW 1.44 1.78 2.56
ω 2.82 1.64 1.72
Tc 1.28 1.26 1.62
Pc 1.51 2.72 4.11
Zc 1.23 1.02 1.20
Vc 1.44 2.11 3.04
Tb 1.36 1.10 1.50
rg 1.39 2.52 3.50
Tm 1.33 1.56 2.07
Ttp 1.33 1.56 2.07
Ptp 27.36 5488.45 200.59
MV 6.64 1.71 3.89
SIG 1.11 1.27 1.41
δ 1.96 1.62 3.16
Vvw 1.43 1.76 2.51
Avw 1.35 1.58 2.14
Pvap 37.89 5.31 201.21
log Kow -7.70 6.31 -13.80
Hvap 1.64 7.31 1.89
d 1.27 7.31 1.57
Mixture property analysis
Following analysis is performed for the mixture from the reactor outlet:
▪ The mixture state or phase (after reaction) – Vapor
▪ State of pure components at mixture conditions and ambient conditions
- Mixture conditions – MeOH, Water, DME - Vapor
- Ambient conditions – MeOH – Liquid, Water – Liquid, DME - Vapor
▪ Azeotropes and pressure sensitivity - None
▪ Liquid-liquid phase splits or eutectic points – None
Page 104
Case Studies
84
Stage II: Base case analysis
As the problem type identified is direct synthesis to generate novel and intensified alternatives,
no base case has been selected, thus stage 2 including step 3 and step 4 is bypassed.
Stage III: Generation of feasible flowsheet alternatives
• Step 5: Generation of mathematical combinatorial superstructure of compounds
The mathematical combinatorial superstructure of compounds is generated by following
algorithm A3.1. The number of compounds is 3 and are annotated as A (MeOH), B (DME)
and C (Water). Minimum number of separation tasks required are 2 to obtain all pure
compounds. This is because any unreacted methanol has to be recycled while the DME
purity should be at least 99.8 mol %. Thus, the superstructure is generated based on all
possible mathematical combinations and is shown in Figure 6.2. The number of possible
flowsheet alternatives at this step are 6.
Figure 6.2: Mathematical combinatorial superstructure of compounds
• Step 6: Identification of principle PBBs
The binary ratio matrix is retrieved from step 2 and thus following the algorithm A3.2,
principle PBBs for all the binary pairs are identified using knowledge base KB3.1 and are
listed in Table 6.3. The PBBs that are not feasible as per mixture phase at ambient or
reaction conditions are removed.
*The separation is using an external solid mass separating agent. Also, note that list in
Table 6.3 is based on a constraint that principle PBBs requiring an external mass
separating agent that further requires an additional separation task are not selected. The
‘M’ PBB is selected by default for all SPBs.
2A B + C-----ABC A/BC
A/CB
C/AB
C/BA
B/C
B/AC
B/CA
A/C
A/B
Reaction taskSeparation
task 1
Separation
task 2
Page 105
6.1. Case study 1: Production of Dimethyl Ether (DME)
85
Table 6.3: Identified list of principle PBBs
Binary
pair
2MeOH → DME + Water
(A → B + C)---ABC--- MeOH/DME (A/B) MeOH/Water (A/C) DME/Water (B/C)
Principle
PBBs
R(V), ES(C) PT(VL), PS(VL) PT(LS), PS(LS), ES(C) PT(VL), PS(VL)
PT(MVV), PS(VV) PT(MVV), PS(VV) PT(MVV), PS(VV)
PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL)
PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)*
• Step 7: Generation of list of feasible SPBs
In this step, a list of feasible SPBs is generated using the PBBs identified in previous steps.
The total number of PBBs identified are M, 2phM, R(V), PC(VL), PT(VL), PS(VL),
PT(MVV), PS(VV), PT(MLL), PS(LL), PT(LS), PS(LS), PT(MVL), PC(LS), PC(VS), PS(VS),
ES(C), ES(H), D - 19.
- S7.1. Operating window for identified PBBs
The operating window of each phenomena is shown in Table 6.4.
Table 6.4: Operating window for all identified PBBs (Pressure – 0.1 MPa)
Phenomena (PBB) Operating Window
M Tlow=131.66 K (lowest melter)
Thigh=373.15 K (highest boiler)
2phM Tlow=131.66 K (lowest melter)
Thigh=373.15 K (highest boiler)
R(V) Tlow=373.15 K (highest boiler)
Thigh=593.15 K (T for reaction from literature)
PC(VL) V-L present
PC(LS) L-S present (solid separating agent)
PC(VS) V-S present (solid separating agent)
PT(VL) Tlow=248.31 K (lowest boiler)
Thigh=373.15 K (highest boiler)
PT(LS) Tlow=131.66 K (lowest melter)
Thigh=273.15 K (highest melter)
PT(MVL) Component affinity
PT(MVV) Component affinity
PT(MLL) Component affinity
PS(LL) L-L present
Page 106
Case Studies
86
PS(VL) V-L present
PS(VV) V-V present (all compounds in vapor phase)
PS(LS) L-S present (can be solid separating agent)
PS(VS) V-S present (solid separating agent)
ES(H) -
ES(C) -
D -
- S7.2. Feasible SPBs
The maximum number of SPBs including both feasible and infeasible are calculated
to be 63003 (from equation 4.2). The list of feasible SPBs generated from identified
PBBs using adjacency matrix and SPB building blocks is shown in Table 6.5. As the
solid phase in’ PC(LS/VS)* and PS(LS/VS)*’ PBBs from Table 6.3 is fixed, the rules are
applied on these PBBs together and are considered different from PT(LS) and PS(LS).
Table 6.5: Generated list of feasible SPBs
SPB Connected PBB Task they may perform
SPB.1 M Mixing
SPB.2 M=2phM Mixing
SPB.3 M=R(V) Mixing+Reaction
SPB.4 M=ES(H) Mixing+Heating
SPB.5 M=ES(C) Mixing+Cooling
SPB.6 M=R(V)=ES(H) Mixing+Reaction+Heating
SPB.7 M=R(V)=ES(C) Mixing+Reaction+Cooling
SPB.8 M=2phM=R(V) Mixing+Reaction
SPB.9 M=2phM=ES(C) Mixing+Cooling
SPB.10 M=2phM=ES(H) Mixing+Heating
SPB.11 M=2phM=R(V)=ES(C) Mixing+Reaction+Cooling
SPB.12 M=2phM=R(V)=ES(H) Mixing+Reaction+Heating
SPB.13 M=2phM=PC(VL)=PT(VL) Mixing+ Phase creation
SPB.14 M=2phM=R(V)=PC(VL)=PT(VL) Mixing+Reaction+Phase creation
SPB.15 M= 2phM=ES(C)=PC(VL)=PT(VL) Mixing+Cooling+ Phase creation
SPB.16 M= 2phM=ES(H)=PC(VL)=PT(VL) Mixing+Heating+ Phase creation
SPB.17 M=2phM=R(V)=ES(C) =PC(VL)=PT(VL) Mixing+Reaction+Cooling+ Phase creation
SPB.18 M=2phM=R(V)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+ Phase creation
SPB.19 M=PT(VL)=PS(VL) Mixing+Separation
SPB.20 M=R(V)=PT(VL)=PS(VL) Mixing+Reaction+Separation
SPB.21 M=ES(C)=PT(VL)=PS(VL) Mixing+Cooling+Separation
Page 107
6.1. Case study 1: Production of Dimethyl Ether (DME)
87
SPB.22 M=ES(H)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.23 M=ES(C)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.24 M=R(V)=ES(H)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.25 M=2phM=PC(VL)=PT(VL)=PS(VL) Mixing+Separation
SPB.26 M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.27 M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.28 M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Separation
SPB.29 M=2phM =R(V)=ES(H) =PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.30 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation
SPB.31 M=PT(MVL)=PS(VL) Mixing+Heating+Separation
SPB.32 M= PT(MVV)=PS(VV) Mixing+Cooling+Separation
SPB.33 M=R(V) =PT(MVV)=PS(VV) Mixing+Reaction+Separation
SPB.34 M=PT(MLL)=PS(LL) Mixing+Cooling+Separation
SPB.35 M=PC(VS)=PS(VS)* Mixing+Separation
SPB.36 M=R(V)=PC(VS)=PS(VS)* Mixing+Reaction+Separation
SPB.37 M=R(V)=ES(C)=PC(VS)=PS(VS)* Mixing+Reaction+Cooling+Separation
SPB.38 M=R(V)=ES(H)=PC(VS)=PS(VS)* Mixing+Reaction+Heating+Separation
SPB.39 M=PC(LS)=PS(LS)* Mixing+Separation
SPB.40 M=ES(H)=PC(LS)=PS(LS)* Mixing+Heating+Separation
SPB.41 M=ES(C)=PC(VS)=PS(VS)* Mixing+Cooling+Separation
SPB.42 M=ES(H)=PC(VS)=PS(VS)* Mixing+Heating+Separation
SPB.43 M=ES(C)=PC(LS)=PS(LS)* Mixing+Cooling+Separation
SPB.44 M=PT(LS)=PS(LS) Mixing+Separation
SPB.45 M=ES(C)=PT(LS)=PS(LS) Mixing+Cooling+Separation
SPB.46 M=ES(H)=PT(LS)=PS(LS) Mixing+Heating+Separation
SPB.47 D Stream division
• Step 8: Generation of phenomena based superstructure
The phenomena based superstructure is generated by using the algorithm A3.3. The
mathematical combinatorial superstructure (Figure 6.2) is combined with principle PBBs
in Table 6.3 to generate phenomena based superstructure. The possible outlet phase is
also identified and marked. Thus, the superstructure generated is shown in Figure 6.3.
Further, the repetitive principle PBBs for same separation with different binary pairs are
removed (for example A/BC and A/CB). These principle PBBs for same binary pairs are
marked with green color (Figure 6.3). The reduced superstructure is shown in Figure 6.4.
• Step 9: Reduction of alternatives and generation of basic structures
- S9.1. Reduction of alternatives
The reduction of alternatives is performed at 3 different levels under feasibility rules
and logical rules.
Page 108
Case Studies
88
Figure 6.3: Generated phenomena based superstructure
2A B + C-----ABC
R(V), ES(C)
A/BC
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/CB
PT(LS), PS(LS), ES(C)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
B/AC
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
B/CA
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/AB
PT(LS), PS(LS), ES(C)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/BA
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
B/C
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/C
PT(LS), PS(LS), ES(C)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/B
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
V-LV-VL-LV-LV-L
V/L
V-LV-VL-LV-LV-L
V/L
L-SV-VL-LV-LV-L
V/L
V-LV-VL-LV-LV-L
V/L
V-LV-VL-LV-LV-L
V/L
L-SV-VL-LV-LV-L
V/L
V
Reaction task Separation task - 1 Separation task - 2
Page 109
6.1. Case study 1: Production of Dimethyl Ether (DME)
89
Figure 6.4: Phenomena based superstructure after removing repetitive principle PBBs
Figure 6.5: Phenomena based superstructure after applying feasibility rules
2A B + C-----ABC
R(V), ES(C)
A/BC
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/CB
PT(LS), PS(LS), ES(C/H)
B/AC
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/AB
PT(LS), PS(LS), ES(C/H)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/BA
PT(VL), PS(VL)
B/C
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/C
PT(LS), PS(LS), ES(C)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/B
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
V-LV-VL-LV-LV-L
V/L
V-LV-VL-LV-LV-L
V/L
L-S
V-L
L-SV-VL-LV-LV-L
V/L
V
Reaction task Separation task - 1 Separation task - 2
2A B + C-----ABC
R(V), ES(C)
A/BC
PT(MVV), PS(VV)PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C)PC(LS/VS), PS(LS/VS)*
B/AC
PT(VL), PS(VL)PT(MVV), PS(VV)
PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C) 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/AB
PT(MVV), PS(VV)PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/BA
PT(VL), PS(VL)
B/C
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/C
PT(LS), PS(LS), ES(C)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/B
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
V-VL-LV-LV/L
V-LV-VL-LV-LV-L
V/L
V-L
V-VL-LV-LV-L
V/L
V
Reaction task Separation task - 1 Separation task - 2
Page 110
Case Studies
90
Feasibility rules
Firstly, the phenomena based superstructure is reduced by applying feasibility
rules at 2 different levels as mentioned in algorithm A3.4. After applying these
rules, the superstructure is reduced as shown in Figure 6.5. Following the
algorithm, the outlet of the reactor is in vapor phase and has no solids present.
Also, there are no non-condensable gases present at outlet. Thus, superstructure
maintains it originality at level 1 reduction rules. Further, looking at phenomena
based feasibility rules at level 2, phenomena with PBB ‘PT(VL)’ under binary pair
A/B and ‘PT(LS)’ under binary pair A/C in ternary mixture of A, B and C is not
feasible according to boiling point and melting point order.
Logical rules
At level 3 reduction (logical rules), the phase of inlet and outlet conditions are
checked and thus, PBBs that does not satisfy the logical rules in algorithm A3.4
are removed. For example, A/BC has outlet in ‘V’ phase, and thus, options with
principle PBBs that only allows ‘L’ feed like ‘PT(MLL), PT(MVL), PC(LS)*’ are
removed in B/C. The updated superstructure is shown in Figure 6.6.
Figure 6.6: Phenomena based superstructure after applying logical rules
2A B + C-----ABC
R(V), ES(C)
A/BC
PT(MVV), PS(VV)PC(VS), PS(VS)*
B/AC
PT(VL), PS(VL)PT(MVV), PS(VV)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(VS), PS(VS)*
C/AB
PT(MVV), PS(VV)PT(MLL), PS(LL), ES(C)PT(MVL), PS(VL), ES(C)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(VS), PS(VS)*
C/BA
PT(VL), PS(VL)
B/C
PT(VL), PS(VL)PT(MVV), PS(VV)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(VS), PS(VS)*
A/C
PT(LS), PS(LS), ES(C)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A/B
PT(VL), PS(VL)PT(MVV), PS(VV)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
V-VV-V
V-LV-VV-L
V-V
V-L
V-VL-LV-LV-L
V-V
V
Reaction task Separation task - 1 Separation task - 2
Page 111
6.1. Case study 1: Production of Dimethyl Ether (DME)
91
- S9.2. Generation of basic structures
The principle PBBs in phenomena-based superstructure (Figure 6.6) are translated to
basic structures using the algorithm A3.5. These basic structures in the form of
superstructure (level 1) is shown in Figure 6.7.
Figure 6.7: Level 1 superstructure with translated principle PBBs to basic structures
• Step 10: Combination of basic structure to generate flowsheet alternatives
The basic structures within the superstructure at level 1 are combined at two different
levels i.e. level 2 and 3 as follows:
Level 2: At level 2, adjacent basic structures within level 1 (Figure 6.7) are considered for
combination following all the generic rules defined in algorithm A3.6. Further in level 2,
two different combinations are performed at level 2a and level 2b. At level 2a, adjacent
A/BC
M=PT(MVV)=PS(VV)
M=PC(VS)=PS(VS)*
2A B + C-----ABC
M=R(V)=ES(C)
B/AC
M=PT(MVV)=PS(VV)
M=PC(VS)=PS(VS)*
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(VL)=PS(VL)
B/C
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(VS)=PS(VS)*
A/C
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(LS)=PS(LS)M=ES(C)
M=PT(MVV)=PS(VV)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PC(VS)=PS(VS)*
M=PC(LS)=PS(LS)*
A/B
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
C/BA
M=PT(VL)=PS(VL)
C/AB
M=PT(MVV)=PS(VV)
M=PC(VS)=PS(VS)*
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
V-V
V-V
V-L
V-V
V-L
V-V
V-V
V-L
V-V
V-L
Reaction task Separation task - 1 Separation task - 2
M=PC(VS)=PS(VS)*
M=PC(LS)=PS(LS)*
V
Page 112
Cas
e S
tud
ies
92
Fig
ure
6.8
: C
om
bin
ati
on
of
ba
sic
stru
ctu
res
at
lev
el
2a
an
d l
ev
el
2b
2A
B
+ C
----
-AB
C
M=
R(V
)=E
S(C
)V
C/A
B--
-A/B
M=
PT
(VL)=
PS
(VL)
M=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VS
)=P
S(V
S)*
M=P
C(M
VV
)=P
S(V
V)
M=
PT
(VL)=
PS
(VL)
M=P
C(V
S)=
PS
(VS
)*M
=P
T(V
L)=
PS
(VL)
M=
PT
(MV
V)=
PS
(VV
)M
=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=E
S(H
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=P
C(V
S)=
PS
(VS
)*M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
B/A
C--
-A/C
M=P
T(V
L)=
PS
(VL)
M=
ES
(C)
M=P
T(L
S)=
PS
(LS
)
M=P
T(V
L)=
PS
(VL)
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=E
S(H
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
PT
(VL)=
PS
(VL)
M=P
C(M
LL)=
PS
(LL)
M=P
T(V
L)=
PS
(VL)
M=
PC
(LS
)=P
S(L
S)*
M=
PT
(MV
V)=
PS
(VV
)M
=P
C(V
S)=
PS
(VS
)*
M=P
T(M
VV
)=P
S(V
V)
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=P
T(M
VL)=
PS
(VL
)
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=P
T(M
LL)=
PS
(LL)
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
PC
(LS
)=P
S(L
S)*
M=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(LS
/VS
)=P
S(L
S/V
S)*
M=E
S(C
)M
=P
T(L
S)=
PS
(LS
)
A/B
C--
-B/C
M=P
C(V
S)=
PS
(VS
)*M
=P
T(M
VV
)=P
S(V
V)
M=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=P
C(V
S)=
PS
(VS
)*M
=2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=P
C(V
S)=
PS
(VS
)*
M=
PT
(MV
V)=
PS
(VV
)M
=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VS
)=P
S(V
S)*
M=P
T(M
VV
)=P
S(V
V)
M=
PC
(VS
)=P
S(V
S)*
Reac
tio
n t
ask
Sep
ara
tio
n t
as
kS
ep
ara
tio
n t
as
kS
ep
ara
tio
n t
as
k
Le
vel
2a
Le
vel
2b
2A
B
+ C
---A
BC
---B
/AC
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
R(V
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
R(V
)=E
S(C
)M
=P
T(M
VV
)=P
S(V
V)
M=
R(V
)=E
S(C
)M
=P
C(V
S)=
PS
(VS
)*
2A
B
+ C
---A
BC
---C
/AB
M=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
R(V
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
R(V
)=E
S(C
)M
=P
T(M
VV
)=P
S(V
V)
M=
R(V
)=E
S(C
)M
=P
C(V
S)=
PS
(VS
)*
2A
B
+ C
---A
BC
---A
/BC
M=R
(V)=
ES
(C)
M=
PT
(MV
V)=
PS
(VV
)
M=
R(V
)=E
S(C
)M
=P
C(V
S)=
PS
(VS
)*
B/C
M=2p
hM=E
S(C
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=P
T(V
L)=
PS
(VL)
M=
PT
(MV
V)=
PS
(VV
)
M=
PC
(VS
)=P
S(V
S)*
A/C
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=
2p
hM=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=P
T(L
S)=
PS
(LS
)M
=E
S(C
)
M=P
T(M
VV
)=P
S(V
V)
M=P
T(M
LL)
=P
S(L
L)
M=P
T(M
VL
)=P
S(V
L)
M=P
C(V
S)=
PS
(VS
)*
M=
PC
(LS
)=P
S(L
S)*
A/B
M=
2p
hM=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)M
=2p
hM=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=2p
hM=E
S(H
)=P
C(V
L)=
PT
(VL
)=P
S(V
L)
M=P
T(V
L)=
PS
(VL)
M=P
T(M
VV
)=P
S(V
V)
M=P
C(V
S)=
PS
(VS
)*
Sep
ara
tio
n t
as
k -
1R
eactio
n -
Sep
aratio
n t
ask
Page 113
6.1. Case study 1: Production of Dimethyl Ether (DME)
93
reaction and separation task are combined to identify feasible combinations while at level
2b, adjacent separation tasks are combined. The feasible combinations at both the levels
are shown in Figure 6.8.
Level 3: At level 3, the superstructures generated at level 2a and 2b are considered for
combination and the combinatorial structures should have same phase or feasible to be
combined with adjacent structures. Thus, using combination rules in algorithm A3.6, the
superstructure performing multiple tasks is shown in Figure 6.9. Also, as the reaction is
an equilibrium reaction, thus the combination of reaction and separation basic structures
removing products may lead to an increased conversion of the reactant making it feasible
to get pure products. For that matter, the combination of reaction and separation task-2
is also considered at level 3.
Figure 6.9: Combination of basic structures at level 3
• Step 11: Translation of the basic structures to unit-operation
The basic structures that perform different identified tasks are then translated to unit
operations using algorithm A3.7 generating process flowsheet alternatives. Table 6.6
gives selected alternatives for the given problem at different levels while Figure 6.10
2A B + C--ABC--A/B/C
M=2phM=ES(C)=PC(V L)=PT(V L)=PS(V L)
M=2phM=R(V)=P C(VL)=P T(VL)=P S(VL)
M=PT(MVV)=PS(VV)
M=2phM=ES(H)=PC(V L)=PT(V L)=PS(V L)
M=PT(MVV)=PS(VV)
M=R(V)=ES(C)
M=PC(VS)=PS(VS)*
M=2phM=ES(C)=PC(V L)=PT(V L)=PS(V L)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=R=PC(LS/VS)=P S(LS/VS)*
M=2phM=P C(VL)=P T(VL)=P S(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(V S)=PS(VS)*
M=R(V)=ES(C)
M=PC(V S)=PS(VS)*
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=P C(VL)=P T(VL)=P S(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(V L)=PS(V L)
Reaction - Separation -
Separation task
Level 3
Reaction - Separation task
2A B + C----B/C
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(V L)=PT(V L)=PS(V L)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=R(V)=E S(C)
M=PT(MVV)=PS(VV)
M=R=PC(VS)=PS(VS)*
Page 114
Case Studies
94
shows some of the basic structures that are translated to unit-operation at level 3. The
complete list of flowsheet alternatives (88 process alternatives) is given in Appendix E.1.
Figure 6.10: Combination of basic structures-(A)-Reactive membrane distillation column, (B)-Reactive membrane adsorption column, (C)-Reactive multistage
adsorption, (D)-Membrane reactor, (E)-Reactive distillation column
DME
Water
MeOH
MeOH
DME
Water
MeOH
Water
DME
MeOH
DME
MeOH
Water
MeOH
DME
Water
MeOH
MeOH
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(VS)=PS(VS)*
M=R(V)=ES(C)
M=PC(VS)=PS(VS)*
M=R(V)=ES(C)
M=PC(VS)=PS(VS)*
M=PT(MVV)=PS(VV)
M=R(V)=ES(C)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
Basic strucutre Unit-operation
(A)
(B)
(C)
(D)
(E)
Page 115
6.1. Case study 1: Production of Dimethyl Ether (DME)
95
Many of the alternatives generated can be found in literature. For example, alternative 14
(Reaction followed by two distillation columns) is the traditional process to produce
DME from methanol (Muller and Hubsch, 2005; Azizi et al., 2014). Alternative 67
(Reactive distillation followed by distillation) and alternative 85 (Reactive divided wall
distillation) are proposed by Kiss and Suszwalak, (2012) while alternative 87 (reactive
distillation) is proposed by Bildea et al. (2017). Some of the alternatives generated are
completely new and have novel unit-operations. Alternative 81 with single unit-operation
i.e. reactive membrane (vapor–permeation) distillation column and alternative 84 with
reactive multi-stage adsorption column are some of the novel solutions generated by the
framework.
An overview of screening of the generated process flowsheet alternatives is given in Figure 6.11.
The total number of mathematical combinations possible are 6. At the phenomena level, it began
with 63003 possible SPB combinations based on selected PBBs. Using principle PBBs, 216
possible flowsheet combinations are identified, which are then screened based on logical and
feasibility rules and further combined based on feasible list of SPBs to generate 88 feasible
flowsheet alternatives for ranking and analysis.
Figure 6.11: Generation and screening of alternatives at different steps
Stage IV: Ranking, analysis and comparison
• Step 12: Ranking and verification of generated flowsheet alternatives
- S12.1. Ranking of unit-operation based flowsheet alternatives
In this step, the generated flowsheet alternatives are ranked in order to identify the
promising one’s that can be further analyzed. The alternatives are ranked based on
the Enthalpy Index (EI) values calculated as described in algorithm A4.1. Table 6.6
shows the top 3 alternatives based on EI values at different levels.
06
63003
216
88
Mathematical
alternatives
All possible
combination of SPB’s
Total number of
alternatives
(feasible + infeasible)
Total number of alternatives
(feasible including novel
and intensified solutions)
Page 116
Case Studies
96
Table 6.6: Top ranked flowsheet alternatives at different levels
Level Alternative
No. Flowsheet alternative EI
3
82 Reactive membrane (vapor) adsorption (water removal) 0.863
84 Reactive multi-stage adsorption 0.860
81 Reactive membrane (vapor) distillation (water removal) 0.462
2
72 Membrane (vapor) reactor (water removal) → VP membrane 1.000
74 Membrane (vapor) reactor (water removal) → Adsorption (MSA(S)) 0.961
61 Membrane (vapor) reactor (DME removal) → VP membrane 0.908
1
26 Reaction → Adsorption (Water-MSA(S)) → VP membrane 0.913
24 Reaction → Adsorption (Water-MSA(S)) → Adsorption (MSA(S)) 0.875
18 Reaction → Adsorption (MeOH-MSA(S)) → VP membrane 0.834
- S12.2. Verification of selected flowsheet alternatives
The top alternatives at different levels are then verified by performing simulations in
PRO/IITM. This is also done to resolve the mass and energy balance of the alternatives,
to verify the key parameters and conduct the post analysis in step 13. Due to lack of
data in literature regarding adsorption and membrane separation for MeOH and
DME removal at the desired process conditions, some of the top alternatives are not
considered for simulation. Thus, simulation is performed for the alternative next in
the ranking while at level 1, traditional alternative of reaction followed by two
distillation columns is selected for further analysis.
o Process alternative 81: This is a novel alternative for the DME production
from methanol with a novel equipment which is yet to be realized in
practicality (Figure 6.12). However, a few similar configurations (without
reactive section) named as distillation-pervaporation in a single unit (DPSU)
are available in literature for this novel equipment being proposed by
Fontalvo and Keurentjes, (2015) and Leon and Fontalvo, (2018). In another
article (Haelssig et al., 2012), a distillation-pervaporation system with internal
membrane was studied and called as membrane dephlegmation process
(MDP). Here in this alternative, unwanted by-product water is removed using
vapor-permeation membrane module within a distillation column and DME
is recovered as distillate while recovered methanol from the bottom is
recycled. The vapor permeation membrane data obtained from Lee et al.
(2004) is used for simulation purposes.
o Process alternative 74: In this process flowsheet (Figure 6.13), water is
removed in the membrane reactor using same vapor permeation membrane
used in process alternative 81. The outlet of membrane reactor containing the
Page 117
6.1. Case study 1: Production of Dimethyl Ether (DME)
97
Figure 6.12: Schematic of process alternative 81 - Reactive DVPSU column
Figure 6.13: Schematic of process alternative 74
Figure 6.14: Schematic of process alternative 14
DME
Water
MeOH
MeOH
MeOH
Water
DME
MeOH
MeOH
Water
MeOH
DME
Page 118
Case Studies
98
DME and unreacted MeOH is then sent to an adsorption column where
MeOH is adsorbed to obtain DME of required purity. The adsorption data for
MeOH is obtained from Rao et al. (2007).
o Process alternative 14: This alternative is the traditional alternative to
produce DME from methanol (EI value-0.33). Here, the reactor is followed by
a sequence of distillation columns to recover DME and send recovered MeOH
back to the reactor (Figure 6.14).
• Step 13: Analysis and comparison of selected flowsheet alternatives
- S13.1. Analysis of selected alternatives
The selected process alternatives are analyzed in terms of economics, sustainability
and life cycle assessment. In-house tools that are part of ICAS (Gani et al. 1997; Gani
2002) is used to perform sustainability (SustainPro) and life cycle analysis (LCSoft).
Selected set of indicators calculated are shown in Table 6.7.
Table 6.7: Analysis of results for selected process flowsheet alternatives
Parameter Alternative 81 Alternative 74 Alternative 14
General results DME Production (kt/y) ∼100 ∼100 ∼100
DME purity (mol %) >99.8 >99.8 >99.8
RM Consumption (kt/y) 142.74 143.04 139.12
RM Cost (M$/y) 61.38 61.51 59.82
RM (MeOH) loss (kt/y) 3.51 3.50 0.05
Energy usage (MJ/hr) 27851.3 23040.0 38878.7
Number of tasks performed 03 03 03
Number of unit operations 01 02 03
Performance metrics DME (kg/kg main RM) 0.701 0.700 0.719
Energy usage (MJ/kg DME) 2.01 1.66 2.80
RM Cost ($/kg DME) 0.614 0.615 0.598
LCA results Carbon footprint (kg CO2/kg DME) 7.04E-03 7.02E-03 1.59E-02
HTPI (1/LD50) 0.103 0.095 0.174
PCOP 0.197 0.182 0.334
HTC (kg benzene eq.) 0.239 0.221 0.405
- S13.2. Comparison of selected alternatives
The comparison of analysis for three selected feasible alternative is given in Table 6.7.
Alternative 81 has the least number of equipment’s as compared to alternative 74 and
the traditional process alternative 14. Flowsheet alternative 74 shows better values of
Page 119
6.1. Case study 1: Production of Dimethyl Ether (DME)
99
the performance parameters in terms of energy, carbon footprint and sustainability
indicators among three. Though, traditional process alternative 14 incur less loss of
MeOH as compared to alternative 81 and 74 owing to membrane separation. A better
membrane in terms of selectivity can further improve performance of novel
intensified equipment and flowsheet alternatives. The membrane area calculated
along with other data is given in Appendix E.2 and E.3. For each of the alternatives
the required product purity is achieved while maintaining the production target.
The results claim the objective set in the beginning of the case study which is the required purity
of DME is achieved with target production. Also, novel, innovative and intensified process
flowsheet alternatives are generated.
6.1.2. Discussion
This case study showcases the capability of developed framework to perform direct process
synthesis-intensification (generation of novel, innovative and intensified solutions without any
prior information and pre-postulation) generating novel, innovative and intensified flowsheet
alternatives. The case study has no prior information and postulation about the kind of
alternatives that can be generated for a target product from a selected raw material. Thus, PBS-
Intensification framework provides a systematic approach to synthesize potentially feasible novel
process options along with innovative solutions.
Since, the primary objective of the framework is to systematically generate potentially feasible
novel unit-operations; for a direct synthesis problem, this case study generates number of
completely novel unit-operation based flowsheets along with existing solutions present in
literature for the production of DME. Table 6.10 presents 3 such novel equipment translated from
phenomena basic structures. Some similar configurations are also available in literature where
for example, adsorption section or membrane module are within the reactor or a distillation
column are replaceable and thus justify the feasibility of such equipment that still needed to be
validated using detailed modelling or by performing experiments.
Page 120
Case Studies
100
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
Toluene being less useful chemical than benzene, most of it is converted to benzene either by
hydrodealkylation or disproportionation reaction. The Hydrodealkylation (HDA) of toluene is a
well-known petrochemical process to produce benzene, where toluene is reacted with hydrogen
to produce benzene along with by products (mainly methane) due to side reactions depending
on the reaction conditions. This method of production for benzene is also called ‘on-purpose’
method as compared to the conventional Benzene-Toluene-Xylene (BTX) extraction processes.
Benzene is one of the most produced and used chemical around the petrochemical industry,
being mainly used to produce cyclohexane that is a nylon precursor.
Objective of the case study: To identify more sustainable, innovative and intensified flowsheet
alternatives for the production of benzene from an existing process flowsheet (Tula, 2016) using
hydrodealkylation of toluene.
6.2.1. Framework application
Stage I: Synthesis analysis
• Step 1: Problem definition
The synthesis problem definition is to produce benzene from hydrodealkylation of
toluene with a purity of at least 99 mol % being one of the design constraint and
performance criteria for this problem. The target annual production of benzene has been
set to 80 kt/y. These parameters are set to be same as existing process flowsheet.
- S1.1. Problem type
The problem type identified is indirect synthesis as an existing process flowsheet is
selected as a base case (Tula, 2016) for HDA of toluene to produce benzene.
- S1.2. Information collection
The same reaction pathway used in the existing process (Tula, 2016) is used in this
problem given as below:
C7H8 + H2 → C6H6 + CH4
2C6H6 ⇌ C12H10 + H2
The hydrodealkylation of toluene can be carried out in different ways i.e. in presence
of the catalyst or homogeneously (Meidanshahi et al., 2011). So, high temperature
reactions can be used instead of using catalysts. The dealkylation reaction for toluene
is exothermic with typical high operating conditions ranging from 500oC to 650oC
around 40 bar. The main reaction at these high operating conditions produces water
and benzene on hydrodealkylation of toluene. There is also a side reaction where
Page 121
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
101
product benzene reacts with another molecule of benzene to form biphenyl and
hydrogen.
• Step 2: Problem analysis
In this step all the necessary reaction, physical property and thermodynamic analysis is
performed which is required for rest of the stages. This is carried in terms of reaction
analysis and mixture analysis.
- S2.1. Reaction analysis
The reaction in step 1 confirms the possibility to produce benzene from hydro-
dealkylation of toluene. The reaction takes place at high temperature and high
pressure in vapor phase. The conversion of the main reaction is 75% (Tula, 2016).
The reaction kinetics can be retrieved from Douglas, (1988). The heat of the reaction
for HDA of toluene reaction is -50.3 kJ/mol, which means the reaction is exothermic
as it is less than zero.
- S2.2. Mixture analysis
The outlet of the reactor consists of 5 components i.e. benzene, biphenyl, methane,
hydrogen and toluene. In this part of step 2, the pure and mixture component analysis
is performed to set up the basis for stage III.
Pure component analysis
The list of pure component properties is retrieved from ICAS database (Gani et
al. 1997; Gani 2002) and literature search. The retrieved list is shown in Table 6.8.
Then, by following the steps A1.1.1-A1.1.2 of algorithm A1.1, the number of binary
pairs are calculated to be 10 as the number of compounds in the problem are
identified to be 5 (Hydrogen, Methane, Toluene, Benzene and Biphenyl). These
components are annotated as A, B, C, D and E respectively. Then, the binary ratio
matrix of pure component properties for binary pairs is calculated using step
A1.1.3 of algorithm A1.1. The binary ratio matrix for selected set of pure component
properties is shown in Table 6.9.
Mixture property analysis
Following analysis is performed for the mixture from the reactor outlet:
▪ The mixture state or phase (after reaction) – Vapor
▪ State of pure components at mixture conditions and ambient conditions
- Mixture conditions
Hydrogen, Methane, Toluene, Benzene and Biphenyl - Vapor
- Ambient conditions
Hydrogen, Methane – Vapor, Toluene, Benzene – Liquid, Biphenyl -
Solid
Page 122
Case Studies
102
▪ Azeotropes and pressure sensitivity - None
▪ Liquid-liquid phase splits or eutectic points – None
Table 6.8: Pure component properties data for the compounds involved in the problem
Property UOM Hydrogen
(A) Methane
(B) Toluene
(C) Benzene
(D) Biphenyl
(E)
MW (g/mol) 2.02 16.00 92.00 78.00 154.00
ω - -0.22 0.01 0.26 0.21 0.37
Tc (K) 33.19 191.00 592.00 562.00 789.00
Pc (bar) 12.96 45.00 41.00 48.00 38.00
Zc - 0.31 0.29 0.26 0.27 0.30
Vc (m3/kmol) 0.06 0.10 0.32 0.26 0.50
Tb (K) 20.39 112.00 384.00 353.00 528.00
dm (Debye) 0.00 0.00 0.36 0.00 0.00
rg (Å) 0.37 1.12 3.47 3.00 4.83
Tm (K) 13.95 90.69 178.18 278.68 342.20
Ttp (K) 13.95 90.69 178.18 278.68 342.20
Ptp (atm) 0.07 0.12 4.18E-07 0.05 9.25E-04
MV (m3/kmol) 0.03 0.04 0.11 0.09 0.16
Hf (kJ/kmol) 0.00 -74520 50170 82880 182420
Gf (kJ/kmol) 0.00 -50490 122200 129600 280230
SIG (kJ/kmol·K) 131.00 186.00 321.00 269.00 394.00
Hfus (kJ/kmol) 117.00 941.00 6636.00 9866.00 18580.00
Hcomb (kJ/kmol) -241820 -802620 -3734000 -3136000 -6031700
δ (√kJ/m3) 6.65 12.00 18.32 18.73 19.26
Vvw (m3/kmol) 0.01 0.02 0.06 0.05 0.09
Avw (m2/kmol) 1.43E+08 2.88E+08 7.42E+08 6.00E+08 1.07E+09
Pvap (Pa) 1.65E+08 6.18 E+07 3.8E+03 1.26E+04 1.19
log Kow - 0.45 1.09 2.69 2.13 4.01
d (pm) 289.0 380.0 585.0 585.0 -
Page 123
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
103
Table 6.9: Binary ratio matrix for the selected set of properties
Binary pair/Property MW Tb Tm Mv δ Vvw Pvap
Hydrogen (A)
Methane (B)
7.94 5.49 6.52 1.31 1.81 2.70 2.67
Toluene (C)
45.93 18.83 12.77 3.79 2.76 9.52 43505.26
Benzene (D)
38.69 17.31 20.00 3.07 2.82 7.62 13120.63
Biphenyl (E)
76.39 25.9 24.52 5.52 2.90 14.6 1.39E+08
Methane (B)
Toluene (C)
5.75 3.43 1.96 2.89 1.53 3.53 16263.76
Benzene (D)
4.88 3.15 3.07 2.34 1.56 2.82 4904.94
Biphenyl (E)
9.63 4.71 3.76 4.21 1.61 5.41 5.19E+07
Toluene (C)
Benzene (D)
1.18 1.09 1.57 1.24 1.02 1.25 3.32
Biphenyl (E)
1.67 1.38 1.92 1.45 1.05 1.53 3191.81
Benzene (D)
Biphenyl (E)
1.97 1.50 1.23 1.80 1.03 1.92 10583.37
Stage II: Base case analysis
The objective of stage II is to analyze the selected base case (Tula, 2016). The base case flowsheet
for HDA of toluene shown in Figure 6.15. In this flowsheet, hydrogen (with 3 mol% of methane
as impurity) and toluene is fed into the reactor operating at high pressure and temperature,
where mentioned reactions takes place. The outlet of the reactor is then flashed after cooling to
recover hydrogen which is recycled to the reactor along with a small purge. The bottom from the
flash then goes through a sequence of distillation columns to recover benzene.
Figure 6.15: Base case flowsheet for HDA of toluene (Tula, 2016)
Page 124
Case Studies
104
The distillate from first distillation column are the gases that were not recovered from flash. The
bottom of second distillation column is then crystallized to obtain crystalline biphenyl while
toluene is sent back to the reactor. A purge ratio of 0.8 is used in base case flowsheet (Tula, 2016).
• Step 3: Generation of task and phenomena based flowsheet
- S3.1. Task based flowsheet
The base case flowsheet shown in Figure 6.15 is translated to task based flowsheet by
identifying unit-operations involved in the process. The unit-operations identified
are reactor, flash column, distillation column and crystallizer. Further, unit-operation
based flowsheet is translated to task based flowsheet using algorithm A2.1. The task
based flowsheet is shown in Figure 6.16.
Figure 6.16: Task based flowsheet for the base case
- S3.2. Phenomena based flowsheet
The phenomena are identified for the unit-operations involved in the base case using
algorithm A2.2. All the unit-operations are known and are present in knowledge base
KB2.1. The phenomena based flowsheet is shown in Figure 6.17. The initial search
space of phenomena identified is M, 2phM, R(V), E(C), ES(H), PC(VL), PT(VL),
PT(LS), PS(VL), PS(LS).
Figure 6.17: Phenomena based flowsheet for the base case
Reaction task
Hydrogen +
Methane
Toluene
Biphenyl
BenzeneFlue gas
PurgeHydrogen + Methane
Separation task Separation task Separation task Separation task
Reaction task
M, R(V), ES(C)
Hydrogen +
Methane
Toluene
Biphenyl
BenzeneFlue gas
PurgeHydrogen + Methane
Separation task
M, 2phM, PC(VL), PS(VL)
Separation task
M, 2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
Separation task
M, 2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
Separation task
M, PT(LS), PS(LS), ES(C)
Page 125
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
105
• Step 4: Identification of additional task and phenomena
- S4.1. Process hotspots and design targets
The process hotspots are identified based on economic, sustainability and life cycle
analysis. These are the raw material loss from the purge stream and is based on high
negative value of material value added for hydrogen and methane. Other process
hotspot is high energy consumption and/or demand based on high utility cost and
CO2 equivalent value from heat exchangers (temperature rise for feed and recycle)
and reboilers of both the distillation column. An overview of sustainability, economic
and life cycle analysis is given in Appendix F. The life cycle analysis is performed using
LCSoft. Further using the Appendix B, following design targets are set based on these
process hotspots:
▪ Reduce raw material loss
▪ Reduce energy consumption
▪ Improvement in LCA/sustainability indicators
▪ Product purity (par on performance criteria)
▪ Production target (par on performance criteria)
- S4.2. Additional task and phenomena
A list of additional task and phenomena are identified based on the process hotspots
using algorithm A2.3 and knowledge base KB2.2. These are shown in Table 6.10.
Table 6.10: Additional task and phenomena to overcome identified process hotspots
Process Hotspot
Main task Binary
pair Phase
Alternative Task
MSA Principle PBBs
Raw material loss
Reaction - V Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
Reaction - V Separation N PT(MVL), PS(VL)
Reaction - V Separation N PT(MVV), PS(VV)
High energy consumption/demand
Separation C/D L Separation Y PC(LL), PT(LL), PS(LL)
Separation C/D L Separation Y PC(LS), PS(LS)
Separation C/D L Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
Separation C/D L Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
Separation C/D L Separation N PT(MVL), PS(VL)
Separation A/B V Separation N PT(MVV), PS(VV)
Separation A/B V Separation Y PC(VS/VL), PS(VS/VL)
These additional list of phenomena in Table 6.10 are added to initial list identified in
step 3 without repetition. Thus, list of phenomena at the end of stage II is as follows:
M, 2phM, R(V), ES(C), ES(H), PC(VL), PC(LL), PC(LS), PT(VL), PT(LS), PT(MVL),
PT(MVV), PT(MLL), PT(LL), PS(VV), PS(LL), PS(VL), PS(LS).
Page 126
Case Studies
106
Stage III: Generation of feasible flowsheet alternatives
• Step 5: Generation of mathematical combinatorial superstructure of compounds
The mathematical combinatorial superstructure of compounds is generated by following
algorithm A3.1. As, the number of compounds are 5 and are annotated as A, B, C, D and
E. Minimum number of separation tasks required are 4 to obtain all pure compounds.
Thus, the superstructure generated based on all possible mathematical combinations is
shown in Figure 6.18. The number of possible alternatives at this step are 39636.
• Step 6: Identification of principle PBBs
The binary ratio matrix is retrieved from step 2 and thus following the algorithm A3.2,
principle PBBs for all the binary pairs are identified using knowledge base KB3.1 and are
listed in Table 6.11. The PBBs that are not feasible as per mixture phase at ambient or
reaction conditions are removed.
Table 6.11: Identified list of principle PBBs
Binary
pair
C + A → D + B, 2D → E + A
(---ABCDE---)
Hydrogen/Methane
(A/B)
Hydrogen/Toluene
(A/C)
Hydrogen/Benzene
(A/D)
Principle
PBBs
R(V), ES(C) PT(MVV), PS(VV) PT(VL), PS(VL) PT(VL), PS(VL)
PC(VS), PS(VS)* PT(MVV), PS(VV) PT(MVV), PS(VV)
PT(MLL), PS(LL) PT(MLL), PS(LL)
PT(MVL), PS(VL) PT(MVL), PS(VL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)*
Binary
pair
Hydrogen/Biphenyl
(A/E)
Methane/Toluene
(B/C)
Methane/Benzene
(B/D)
Methane/Biphenyl
B/E
Principle
PBBs
PT(VL), PS(VL) PT(VL), PS(VL) PT(VL), PS(VL) PT(VL), PS(VL)
PT(MVV), PS(VV) PT(MVV), PS(VV) PT(MVV), PS(VV) PT(MVV), PS(VV)
PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL)
PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)* PC(LS/VS), PS(LS/VS)*
Binary
pair
Toluene/Benzene
C/D
Toluene/Biphenyl
C/E
Benzene/Biphenyl
D/E
Principle
PBBs
PT(LS), PS(LS), ES(C/H) PT(LS), PS(LS), ES(C/H) PT(LS), PS(LS), ES(C/H)
PT(MVL), PS(VL) PT(VL), PS(VL) PT(VL), PS(VL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H) PT(MVV), PS(VV)
PT(MVV), PS(VV)
PC(LS), PS(LS)
PC(LS), PS(LS)* PT(MVL), PS(VL) PT(MVL), PS(VL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
PC(LS), PS(LS)* PC(LS), PS(LS)*
Page 127
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
107
Figure 6.18: Mathematical combinatorial superstructure of compounds
A + C B + D
2D A + E
--ABCDE--
A/BCDE
B/ACDE
E/ABCD
AB/CDE
C/ABDE
D/ABCE
AC/BDE
AD/BCE
BD/ACE
BE/ACD
AE/BCD
BC/ADE
CD/ABE
CE/ABD
DE/ABC
ABCD A/BCD
A/CBD
AB/DC
BA/CD
A/DBC
AB/CD
BA/DC
AC/BD
CA/DB
AD/BC
AC/DB
CA/BD
AD/CB
DA/BC
DA/CB
B/ACD
B/CDA
B/DAC
C/ABD
C/BDA
C/DBA
D/ABC
D/BCA
D/CAB
CDE
B/CD
B/DC
C/BD
C/DB
D/BC
D/CB
A/CD
A/DC
C/AD
C/DA
D/AC
D/CA
A/BD
A/DB
B/AD
B/DA
D/AB
D/BA
A/BD
A/DB
B/AD
B/DA
D/AB
D/BA
C/D
B/D
B/C
A/D
A/C
A/B
C/D
B/D
A/D
A/B
B/D
A/D
A/B
C/D
A/C
B/D
A/D
C/B
C/ED
CD/E
C/DE
DC/E
D/CE
D/EC
D/E
C/D
C/E
10*6
5*4
A/B
Page 128
Case Studies
108
*The separation is using an external mass separating agent. Also, note that list in Table 6.11 is
based on a constraint that principle PBBs requiring an external mass separating agent that
further requires an additional separation task are not selected.
• Step 7: Generation of list of feasible SPBs
In this step, a list of feasible SPBs is generated using the PBBs identified in previous
steps. The total number of PBBs identified are M, 2phM, R(V), ES(C), ES(H), PC(VL),
PC(LS), PC(VS), PT(VL), PT(LS), PT(MVL), PT(MVV), PT(MLL), PS(VV), PS(LL),
PS(VL), PS(LS), PS(VS), D - 19.
- S7.1. Operating window for identified PBBs
The operating window of each phenomena is shown in Table 6.12.
Table 6.12: Operating window for all identified PBBs
Phenomena (PBB) Operating Window
M Tlow=13.95 K (lowest melter)
Thigh=850.00 K (highest reaction temperature from literature)
2phM Tlow=13.95 K (lowest melter)
Thigh=850.00 K (highest reaction temperature from literature)
R(V)
P= 40 bar (reaction pressure from literature)
Thigh=528.00 K (highest boiler)
Thigh=850.00 K (highest reaction temperature from literature)
PC(VL) V-L present (also liquid separating agent)
PC(LS) L-S present (solid separating agent)
PC(VS) V-S present (solid separating agent)
PT(VL) Tlow=20.39 K (lowest boiler)
Thigh=528.00 K (highest boiler)
PT(LS) Tlow=13.95 K (lowest melter)
Thigh=342.00 K (highest melter)
PT(MVL) Component affinity
PT(MVV) Component affinity
PT(MLL) Component affinity
PS(VL) V-L present
PS(VV) V-V present (all compounds in vapor phase)
PS(LS) L-S present (can be solid separating agent)
PS(LL) L-L present (liquid separating agent)
PS(VS) V-S present (solid separating agent)
Page 129
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
109
ES(H) -
ES(C) -
D -
- S7.2. Feasible SPBs
The maximum number of SPBs including both feasible and infeasible are calculated
to be 63003 (from equation 4.2). The list of feasible SPBs generated from identified
PBBs using adjacency matrix and SPB building blocks is shown in Table 6.13. The
combination rules are applied together for principle PBBs with MSA’s.
Table 6.13: Generated list of feasible SPBs
SPB Connected PBB Task they may perform
SPB.1 M Mixing
SPB.2 M=2phM Mixing
SPB.3 M=R(V) Mixing+Reaction
SPB.4 M=ES(H) Mixing+Heating
SPB.5 M=ES(C) Mixing+Cooling
SPB.6 M=R(V)=ES(H) Mixing+Reaction+Heating
SPB.7 M=R(V)=ES(C) Mixing+Reaction+Cooling
SPB.8 M=2phM=R(V) Mixing+Reaction
SPB.9 M=2phM=ES(C) Mixing+Cooling
SPB.10 M=2phM=ES(H) Mixing+Heating
SPB.11 M=2phM=R(V)=ES(C) Mixing+Reaction+Cooling
SPB.12 M=2phM=R(V)=ES(H) Mixing+Reaction+Heating
SPB.13 M=2phM=PC(VL)=PT(VL) Mixing+ Phase creation
SPB.14 M=2phM=R(V)=PC(VL)=PT(VL) Mixing+Reaction+ Phase creation
SPB.15 M= 2phM=ES(C)=PC(VL)=PT(VL) Mixing+Cooling+ Phase creation
SPB.16 M= 2phM=ES(H)=PC(VL)=PT(VL) Mixing+Heating+ Phase creation
SPB.17 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL) Mixing+Reaction+Cooling+ Phase creation
SPB.18 M=2phM=R(V)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+ Phase creation
SPB.19 M=PT(VL)=PS(VL) Mixing+Separation
SPB.20 M=R(V)=PT(VL)=PS(VL) Mixing+Reaction+Separation
SPB.21 M=ES(C)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.22 M=ES(H)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.23 M=R(V)=ES(H)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.24 M=R(V)=ES(C)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation
SPB.25 M=2phM=PC(VL)=PT(VL)=PS(VL) Mixing+Separation
SPB.26 M=2phM=ES(H)= PC(VL)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.27 M=2phM=ES(C) =PC(VL)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.28 M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Separation
SPB.29 M=2phM =R(V)=ES(H) =PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.30 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation
Page 130
Case Studies
110
SPB.31 M=PT(MVL)=PS(VL) Mixing+Heating+Separation
SPB.32 M= PT(MVV)=PS(VV) Mixing+Cooling+Separation
SPB.33 M=R(V) =PT(MVV)=PS(VV) Mixing+Reaction+Separation
SPB.34 M=PT(MLL)=PS(LL) Mixing+Cooling+Separation
SPB.35 M=PC(VS)=PS(VS)* Mixing+Separation
SPB.36 M=R(V)=PC(VS)=PS(VS)* Mixing+Reaction+Separation
SPB.37 M=R(V)=ES(C)=PC(VS)=PS(VS)* Mixing+Reaction+Cooling+Separation
SPB.38 M=R(V)=ES(H)=PC(VS)=PS(VS)* Mixing+Reaction+Heating+Separation
SPB.39 M=PC(LS)=PS(LS)* Mixing+Separation
SPB.40 M=ES(H)=PC(LS)=PS(LS)* Mixing+Heating+Separation
SPB.41 M=ES(C)=PC(VS)=PS(VS)* Mixing+Cooling+Separation
SPB.42 M=ES(H)=PC(VS)=PS(VS)* Mixing+Heating+Separation
SPB.43 M=ES(C)=PC(LS)=PS(LS)* Mixing+Cooling+Separation
SPB.44 M=PT(LS)=PS(LS) Mixing+Separation
SPB.45 M=ES(C)=PT(LS)=PS(LS) Mixing+Cooling+Separation
SPB.46 M=ES(H)=PT(LS)=PS(LS) Mixing+Heating+Separation
SPB.47 D Stream division
• Step 8: Generation of phenomena based superstructure
The phenomena based superstructure is generated by using the algorithm A3.3. The
mathematical combinatorial superstructure (Figure 6.18) is combined with principle
PBBs from Table 6.11 to generate phenomena based superstructure. The possible outlet
phase is also identified and marked. As, hydrogen (A) and methane (B) gases are non-
condensable, the first task is selected as removal of these non-condensable gases and thus
choosing relevant sub superstructure from Figure 6.18, phenomena based superstructure
is generated as shown in Figure 6.19.
Further, the repetitive principle PBBs for same separation with different binary pairs are
removed (for example AB/CDE, AB/DCE, AB/ECD, BA/CDE, BA/DCE and BA/ECD).
These principle PBBs for same binary pairs are marked with green color (Figure 6.19). The
reduced superstructure is shown in Figure 6.20.
• Step 9: Reduction of alternatives and generation of basic structures
- S9.1. Reduction of alternatives The reduction of alternatives is performed at 3 different levels under feasibility rules
and logical rules.
Feasibility rules
Firstly, the phenomena based superstructure is reduced by applying feasibility
rules at 2 different levels using algorithm A3.4. Following algorithm, the outlet of
the reactor is in vapor phase and has no solids present. Thus, the superstructure
maintains it originality at level 1 reduction rules. Further, looking at phenomena
Page 131
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
111
based feasibility rules at level 2, phenomena with PBB ‘PT(VL)’ under binary pairs
C/E, C/D and ‘PT(LS)’ under binary pair D/E in ternary mixture of C, D and E are
not feasible according to boiling point and melting point order.
Figure 6.19: Generated phenomena based superstructure
L-SV-LV-VV-LV-L
V-L
L-SV-LV-VL-SV-LV-L
V-L
L-SV-LV-VV-LV-L
V-L
L-SV-LV-VL-SV-LV-L
V-L
L-SV-LV-L
V-L
L-SV-LV-L
V-L
C/DE
PT(LS), PS(LS), ES(C)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/ED
PT(LS), PS(LS), ES(C)PT(VL), PS(VL)
PT(MVV), PS(VV)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
CD/E
PT(LS), PS(LS), ES(C)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
DC/E
PT(LS), PS(LS), ES(C)PT(VL), PS(VL)
PT(MVV), PS(VV)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
D/CE
PT(LS), PS(LS), ES(C)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
D/EC
PT(LS), PS(LS), ES(C)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
D/E
PT(LS), PS(LS), ES(C/H)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/D
PT(LS), PS(LS), ES(C/H)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/E
PT(LS), PS(LS), ES(C/H)PT(VL), PS(VL)
PT(MVV), PS(VV)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
R(V), ES(C)
AB/CDE
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
AB/DEC
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
AB/ECD
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
BA/CDE
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
BA/DEC
PT(VL), PS(VLPT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
BA/ECD
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A + C B + D
2D A + E
--ABCDE-- V-LV-VL-LV-LV-L
V-L
V-LV-VL-LV-LV-L
V-L
V-LV-VL-LV-LV-L
V-L
V-LV-VL-LV-LV-L
V-L
V-LV-VL-LV-LV-L
V-L
V-LV-VL-LV-LV-L
V-L
V
Reaction task Separation task - 1 Separation task - 2 Separation task - 3
A/B
PT(MVV), PS(VV)PC(VS), PS(VS)*
Page 132
Case Studies
112
Figure 6.20: Phenomena based superstructure after removing repetitive principle PBBs
Logical rules
At level 3 reduction (logical rules), the phase of inlet and outlet conditions are
checked and thus, PBBs that does not satisfy the logical rules in algorithm A3.4
are removed. For example, outlet mixture from reactor is in ‘V’ phase, and thus,
options with principle PBBs that only allows ‘L’ feed like ‘PT(MLL), PT(MVL),
PC(LS)*’ are removed in first separation task.
The updated superstructure after all reductions is shown in Figure 6.21.
- S9.2. Generation of basic structures The principle PBBs in phenomena-based superstructure (Figure 6.21) are translated
to basic structures using the algorithm A3.5. These basic structures in the form of
superstructure (level 1) is shown in Figure 6.22.
V-LV-V
L-SV-LV-VL-SV-LV-L
V-L
L-SV-LV-VL-SV-LV-L
L-SV-LV-L
V-L
V-L
C/DE
PT(LS), PS(LS), ES(C)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/ED
PT(VL), PS(VL)PT(MVV), PS(VV)
CD/E
PT(LS), PS(LS), ES(C)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
D/CE
PC(LS/VS), PS(LS/VS)*
D/EC
PT(LS), PS(LS), ES(C)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
D/E
PT(LS), PS(LS), ES(C/H)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/D
PT(LS), PS(LS), ES(C/H)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/E
PT(LS), PS(LS), ES(C/H)PT(VL), PS(VL)
PT(MVV), PS(VV)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
R(V), ES(C)
AB/CDE
PT(VL), PS(VL)PT(MVV), PS(VV)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A + C B + D
2D A + E
--ABCDE-- V-LV-VL-LV-LV-L
V-L
V
Reaction task Separation task - 1 Separation task - 2 Separation task - 3
A/B
PT(MVV), PS(VV)PC(VS), PS(VS)*
Page 133
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
113
Figure 6.21: Phenomena based superstructure after applying reduction rules
• Step 10: Combination of basic structure to generate flowsheet alternatives
The basic structures within the superstructure at level 1 are combined at two different
levels i.e. level 2 and 3 as follows:
Level 2: At level 2, adjacent basic structures within level 1 (Figure 6.7) are considered for
combination following all the generic rules defined in algorithm A3.6. Further in level 2,
three different combinations are performed at level 2a, 2b and 2c. At level 2a, adjacent
reaction and separation task are combined to identify feasible combinations while at level
2b, adjacent separation task are combined. The feasible combinations in the form of
superstructure are shown in Appendix F.2.
Level 3: At level 3, the superstructures generated at level 2a, 2b and 2c are considered for
combination and the combinatorial structures should have same phase or feasible to be
combined with adjacent structures. Thus, using combination rules in algorithm A3.6, the
superstructure performing multiple tasks is shown in Appendix F.3.
V-V
L-SV-LV-VL-SV-LV-L
V-L
V-LV-VL-SV-LV-L
L-SV-LV-L
V-L
C/DE
PT(LS), PS(LS), ES(C)PT(MVL), PS(VL)
PC(LS/VS), PS(LS/VS)*
C/ED
PT(MVV), PS(VV)
CD/E
PT(LS), PS(LS), ES(C)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
D/CE
PC(LS/VS), PS(LS/VS)*
D/EC
PT(VL), PS(VL)PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
D/E
PT(LS), PS(LS), ES(C/H)PT(VL), PS(VL)
PT(MVV), PS(VV)PC(LS), PS(LS)
PT(MVL), PS(VL)2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/D
PT(LS), PS(LS), ES(C/H)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
C/E
PT(LS), PS(LS), ES(C/H)PT(VL), PS(VL)
PT(MVV), PS(VV)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
R(V), ES(C)
AB/CDE
PT(VL), PS(VL)PT(MVV), PS(VV)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PC(LS/VS), PS(LS/VS)*
A + C B + D
2D A + E
--ABCDE--V-LV-VV-L
V-L
V
Reaction task Separation task - 1 Separation task - 2 Separation task - 3
A/B
PT(MVV), PS(VV)PC(VS), PS(VS)*
Page 134
Case Studies
114
Figure 6.22: Level 1 superstructure with translated principle PBBs to basic structures
• Step 11: Translation of the basic structures to unit-operation
The basic structures that perform different identified tasks are then translated to unit
operations using algorithm A3.7 generating process flowsheet alternatives. Table 6.14
gives selected alternatives for the given problem at different levels while Figure 6.23
shows some of the basic structures that are translated to unit-operation. The complete
list of flowsheet alternatives generated is given in Appendix F.4.
Many of the alternatives generated are available in literature. For example, alternative 118
(Reaction followed by flash and multiple distillation column to separate benzene and the
A + C B + D
2D A + E
--ABCDE--
M=R(V)=ES(C)
C/DEAB/CDE
C/ED
D/E
C/D
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS)=PS(VS)*
M=PT(MVV)=PS(VV)
M=PT(MVL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)M=ES(C/H)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
D/EC
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(LS)=PS(LS)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
CD/E
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(LS)=PS(LS)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)M=ES(C)
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(LS)=PS(LS)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)M=ES(C/H)
C/E
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)M=ES(C/H)
V-L
V-L
V-L
V-L
V-V
V
L-S
V-V
V-L
V-L
D/CE
M=PT(LS)=PS(LS)M=ES(C)
L-S
M=PC(VS/LS)=PS(VS/LS)* V-L
V-V
V-L
L-S
V-L
V-L
V-L
L-S
V-V
V-L
V-L
Reaction task Separation task - 1 Separation task - 2 Separation task - 3
A/B
M=PT(MVV)=PS(VV)
M=PC(VS)=PS(VS)*
Page 135
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
115
Figure 6.23: Combination of basic structures-(A)-Cooling crystallizer, (B)-Distillation column, (C)-Membrane distillation column (DPVSU), (D)-Reactive divided wall column
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
Basic strucutre Unit-operation
(A)
(B)
(C)
(D)Toluene + Biphenyl
Toluene + H2
Methane + H2
Benzene
Toluene + Biphenyl
Toluene
Biphenyl
Benzene
Methane + H2
Toluene, H2,
Methane, Benzene, Biphenyl,
Toluene + Biphenyl
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
Toluene
Biphenyl
Toluene+ Biphenyl
Page 136
Case Studies
116
toluene) is proposed by Douglas, (1985). Alternative 118 including membrane to separate
purged non condensable and recycling them to reactor is proposed by Bouton and
Luyben, (2008). While, Konda et al. (2006), proposed a similar alternative to Bouton and
Luyben, (2008) where membrane is used to recover hydrogen directly from flash outlet
in place of purged stream. Some of the generated alternatives (493-514, 530-549, 593-
616) including reactive distillation are also studied in literature (Shah et al., 2012).
An overview of screening of the generated process flowsheet alternatives is given in Figure 6.24.
The total number of mathematical combinations possible are 39636. At the phenomena level, it
began with 63003 possible SPB combinations based on selected PBBs. Using principle PBBs
20304 possible flowsheet combinations were identified which were then screened based on
redcutuon and feasibility rules and further combined based on feasible list of SPBs to generate
726 feasible flowsheet alternatives for ranking and analysis.
Figure 6.24: Generation and screening of alternatives at different steps
Stage IV: Ranking, analysis and comparison
• Step 12: Ranking and verification of generated flowsheet alternatives
- S12.1. Ranking of unit-operation based flowsheet alternatives The flowsheet alternatives generated in stage 3 of the framework are ranked based on
calculated Enthalpy Index (EI) values. The top alternatives at different levels are
highlighted in Table 6.14.
- S12.2. Verification of selected flowsheet alternatives
The selected alternatives are verified by performing simulations in PRO/IITM and
Aspen PlusTM. Due to unavailability of data regarding separation using membrane and
adsorption at required conditions for benzene, toluene and biphenyl, the alternatives
further having lower Enthalpy Index (EI) value are selected. The alternatives selected
at different levels are further analyzed.
39636
63003
13536
726
Mathematical
alternatives
All possible
combination of SPB’s
Total number of
alternatives
(feasible + infeasible)
Total number of alternatives
(feasible including novel
and intensified solutions)
Page 137
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
117
Table 6.14: Top ranked flowsheet alternatives at different levels
Level Alternative
No. Flowsheet alternative EI
3 718 Reaction→Multistage membrane (vapor) adsorption (gases removal) 0.981
726 Reaction→Multistage adsorptive (gases removal) membrane 0.971
2 582 Membrane reactor (gases removal) → VP membrane → Adsorption (MSA(S)) 0.968
579 Membrane reactor (gases removal) → VP membrane → VP membrane 0.982
1 33 Reaction → Adsorption (MSA(S)) → VP membrane → Adsorption (MSA(S)) 1.000
37 Reaction → Adsorption (MSA(S)) → Adsorption (MSA(S)) → Adsorption-MSA(S) 0.999
o Alternative 118 (hydrogen/methane separation using gas membrane):
The selected alternative resembles the base case flowsheet except the mixture
of unreacted hydrogen and methane (unwanted by product) are recycled to
the reactor. Here, this mixture which is also the cause of highest energy
consumption and utility cost among all the heat exchangers in base case is
separated using membrane at the purge stream. The membrane data is
adapted from the process alternatives suggested by Konda et al. (2006) and
Fischer and Iribarren, (2011). An extra stabilizer column is required as non-
condensable are not completely removed from the flash. The schematic of this
alternative is shown in Figure 6.25.
Figure 6.25: Schematic of process alternative 118
o Alternative 272: In this alternative, the benzene, toluene and biphenyl are
separated using divided wall column (DWC). The DWC is simulated using
petlyuk column in Aspen PlusTM. The schematic of the alternatives is shown
in Figure 6.26. The separation of the non-condensable hydrogen and methane
using membrane is also considered as in alternative 118.
Hydrogen +
Methane
Toluene
Toluene
Biphenyl
BenzeneFlue gas
Methane
Hydrogen + Methane
Page 138
Case Studies
118
Figure 6.26: Schematic of process alternative 272
Besides, these alternatives, other process flowsheets at level 3 incorporating reactive distillation
with high EI value followed by distillation or crystallization can also be analyzed. In this case
study, the analysis is performed limiting to level 1 and level 2 alternatives.
• Step 13: Analysis and comparison of selected flowsheet alternatives
- S13.1. Analysis of selected alternatives
The selected process alternatives are analyzed in terms of economics, sustainability
and life cycle assessment using in-house tools. An indicative analysis for the selected
alternatives along with the base case is shown in Table 6.15.
- S13.2. Comparison of selected alternatives
The comparison of analysis for selected feasible alternatives is given in Table 6.15.
Both alternatives are novel process flowsheets to produce benzene from
hydrodealkylation of toluene. These alternatives are more sustainable and economic
than the base case and also shows improvement in LCA indicators.
In selected alternatives, an additional task as compared to the base case is added in terms of
membrane to separate methane from recycle stream. This is to reduce the amount of purge and
thus reduction of hydrogen loss. Addition of this gas membrane reduces the annual hydrogen
loss by around 97 %. Overall benzene production also increases owing to better recovery of
hydrogen. The energy consumption reduces in both the alternatives. The value of LCA indicators
has better values than base case (performed using LCSoft for all the alternatives including base
case). The membrane area calculated along with other data is given in Appendix F.5. A better
membrane in terms of flux or permeability can further improve performance of novel and
intensified flowsheet alternatives. For each of the alternatives, product purity is above required
while approximately achieving annual production target. A graphical comparison of three
selected alternatives is shown in Figure 6.27. Due to considerably large reduction in hydrogen
loss, a factor of 20 is taken for Figure 6.27.
Hydrogen +
Methane
Toluene
Toluene
Flue gas
Biphenyl
Benzene
Methane
Hydrogen + Methane
Page 139
6.2. Case study 2: Hydrodealkylation (HDA) of Toluene
119
Table 6.15: Analysis of results for selected process flowsheet alternatives
Parameter Base case Alternative 118 Alternative 272
General results Benzene production (kt/y) ∼80 ∼80 ∼80
Benzene purity (mol %) >99 >99 >99
RM Consumption (Mt/y) 106.02 102.98 103.00
RM Cost (M$/y) 21.22 18.06 18.06
RM (H2) loss (kt/y) 2538.24 82.78 82.78
Total heating energy (M KJ/hr) 34.57 34.22 33.42
Total cooling energy (M KJ/hr) 43.67 36.17 33.65
Number of tasks performed 4 4 4
Number of unit operations 5 6 5
Performance
metrics
Benzene (kg/kg RM) 0.75 0.77 0.78
Energy usage (MJ/kg Benzene) 7.91 7.10 6.70
RM Cost ($/kg Benzene) 0.27 0.23 0.23
LCA results Carbon footprint (CO2 equivalent) 0.94 0.90 0.87
HTPI (1/LD50) 51.05 16.72 16.72
HTPE 47.78 15.30 15.30
ATP 59.20 57.54 57.54
GWP 7.90 7.82 7.82
Further, recalling the design targets set in step 4, which are required to be met in order to achieve
more sustainable, economic and innovative solutions. These are as follows:
- Reduce raw material loss – Yes (96 % reduction annually)
- Reduce energy consumption – Yes (10-15 % reduction per kg of product)
- Improvement in LCA/sustainability indicators – Yes (1-67 % reduction)
- Product purity (par on performance criteria) – Yes (achieved as required)
- Production target (par on performance criteria) – Yes (achieved as required)
6.2.2. Discussion
This case study showcases the capability of developed framework to perform indirect process
synthesis-intensification (generation of the more economic, sustainable, novel and intensified
process alternatives for an existing process). The base case is selected from literature which is
analysed in stage 2 to generate better alternatives. The alternatives generated are novel and has
Page 140
Case Studies
120
better sustainability and economics than the base case. Thus, PBS-Intensification framework
provides a systematic approach to synthesize potentially feasible novel and innovative process
options that are better than the existing process or the base case.
As, primary objective of the framework is to systematically generate potentially feasible novel
unit-operations; for an indirect synthesis problem, this case study generates number of novel
unit-operation based flowsheets along with existing solutions present in literature for the
hydrodealkylation of toluene. Alternatives including reactive distillation column at level 3 can
be further analysed with other adjacent unit-operations. A study by Shah et al. (2012) shows that
using reactive distillation column for HDA of toluene at high pressure balances out the effect of
flowsheet simplification with less unit operations by carrying out separations at high pressure
within the RD column. Still, RD column possess the potential for significant reduction and
simplification for HDA reactions that can be carried out at lower pressures.
Figure 6.27: Comparison of performance criteria for alternatives relative to base case
60%
70%
80%
90%
100%
Benzene(kg/Kg main RM)^-1
RM Consumption (Mt/y)
Total cooling energy (M KJ/hr)
Total heating energy (M KJ/hr)RM Cost (M$/kg product)
Carbon footprint (CO2equivalent)
RM (H2) loss (kt/y)
Base Case Alternative 137 Alternative 324
Page 141
6.3. Case study 3: Production of Bio-Succinic Acid
121
6.3. Case study 3: Production of Bio-Succinic Acid
Succinic acid, a four-carbon dicarboxylic acid is one of the most widely used platform chemical
and is a precursor to produce different chemicals with application in food, pharma and various
other chemical sectors (Song et al., 2006). Its demand is rising exponentially and is projected to
reach 247.9 thousand ton (t) by 2021 (Technavio, 2018). Moreover, increasing interest in
sustainability along with dynamic situation of petrochemical industry has created attraction
towards production of bio-chemicals such as succinic acid. Alongside this, the production of bio-
succinic acid is favorable for reduction of carbon footprint since it uses CO2 as an additional
carbon source. It also possesses great potential to replace chemicals like phthalic anhydride and
adipic acid used in plasticizers and polyurethanes – both very big scale bulk chemicals.
Objectives of the case study:
• To identify novel, innovative and intensified process alternatives for the production of
bio-succinic acid utilizing CO2.
In this case study, the base case flowsheet has been synthesized and designed to generate data
required for intensification. The base case is first synthesized in order to cover the wide range of
possibilities in fermentation technique involving different bacterial and yeast strains. Also,
several downstream technologies have been published in literature to obtain pure succinic acid
and thus superstructure based mathematical optimization is performed to identify an optimal
processing route for intensification.
6.3.1. Synthesis and design using superstructure based optimization
The objective of this section to identify an optimal process flowsheet (base case) for the
production of bio-succinic acid using superstructure based optimization approach. The optimal
process flowsheet is then designed and analyzed to identify possible targets of improvement to
be achieved using intensification.
General problem definition
The general synthesis problem for this case study is to find an optimal processing route among
numerous alternatives for production of bio-succinic acid with a purity of at least 99 wt. %
(pharmaceutical grade). Additionally, basic information about succinic acid (product), its raw
material(s), target production, reaction information for example conversion is also collected.
Some of the major producers of bio-succinic acid are Bio Amber Inc (joint venture of DNP Green
Technology and ARD), Reverdia (joint venture of DSM and Roquette), Myriant Corporation and
Succinity (joint venture of BASF and Corbion Purac) (Choi et al., 2015). The production plant
owned by Bio Amber in Sarnia (Canada) has the highest capacity of 30 kilo ton per year (kt/y)
Page 142
Case Studies
122
(Cavani et al., 2016). Thus, the production target for this case study is set to produce 30 kt/y of
succinic acid. Over the last 30 years, the production of bio-succinic acid has been the subject of
interest to many researchers and industries (Mckinlay et al., 2007; Bechthold et al., 2008). Thus,
there are diverse options proposed in literature in building a process for bio-succinic acid
production. Traditionally, biochemical processes are designed around the best choice of host
organism. But a process is called successful if it can be applied commercially with optimized
capital and operating costs. This includes host micro-organism, biochemical pathway,
fermentation conditions and downstream process. Two distinctive solutions based on the pH of
the fermentation broth have been identified as most common across various research and
patented articles (Table 6.16). Fermentation using bacterial strains are conducted at neutral pH
and are often capable of producing high yield. Though bacterial fermentation for succinic acid
tend to have complex downstream process as it requires splitting of succinate salt to form
succinic acid and inorganic salt coproduct. Another solution focuses on acidophilic yeast
fermentations that operate below the lower pKa value of succinic acid (4.2), that increases the
ratio of succinic acid to succinate salts simplifying the downstream process but do not generally
give substantial yield and productivity. Thus, both type of processes is considered.
Bio-based succinic acid has an attractive theoretical yield of 1.124 g/g of glucose and 1.283 g/g of
glycerol (greater than 1 because of CO2 as extra carbon source), which is the highest among bio-
based chemicals. This leads to an efficient use of feedstocks, less volatility and lower raw material
costs. Thus, based on the attractive theoretical yield, along with Glucose and Glycerol, four
different raw materials (Glucose, Glycerol, Maltose and Sucrose) are considered. As defined in
objective, only those fermentations are considered that uses CO2 as the raw material. This is due
to the following two reasons; it acts as an additional carbon source and secondly a sustainable
solution to reduce carbon footprint. An example of abstract sustainable scheme for production
of bio-succinic acid in presence of bacteria or yeast is shown in Figure 6.28.
Figure 6.28: An example of abstract reaction scheme for bio-succinic acid
The production of bio-succinic acid can be carried out using different feedstocks and several
micro-organisms. A lot of research has been done to identify the best strains giving optimal yield,
high concentration and high productivity. Some of the example of different micro-organisms
used are Actinobacillus succinogenes (Guettler et al., 1999), Saccharomyces cerevisiae (Raab et
al., 2010), Mannheimia succiniciproducens (Lee et al., 2002), Corynebacterium glutamicum
(Okino et al., 2005; Litsanov et al., 2012), Yarrowia lipolytica (Yuzbashev et al., 2010),
Anaerobiospirillum succiniciproducens (Lee et al., 2003), Bacteroides fragilis (Isar et al., 2007),
C6H12O6 + CO2 C4H6O4 + CH3COOH + HCOOH
Formic acid (By product)
Glucose (main raw mateiral)
Carbon dioxide (Additional carbon source)
Succinic acid (main product)
Bacteria or Yeast
Acetic acid (By product)
Page 143
6.3. Case study 3: Production of Bio-Succinic Acid
123
Prevotella ruminicola and Ruminobacter amylophilus (Geuttler, Jain and Soni, 1998), Fibrobacter
succinogenes (Li et al., 2010), Basfia succinoproducens (Scholten et al., 2009) and Escherichia
coli (Donnelly et al., 1998; Sanchez et al., 2005, Jantama et al., 2008). A list of fermentation and
related data based on the type of host micro-organism, raw material, yield, productivity and
broth concentration is collected (Table 6.16). The data mentioned in table is either directly taken
from the mentioned references or is calculated based on the information given. Note that the
list includes only those fermentations that utilizes CO2 as an additional carbon source.
Table 6.16: Fermentation data to produce bio succinic acid using different strains
(FERM-1: Datta, Glassner, Jain and Roy, (1992); FERM-2: Glassner and Datta, (1992); FERM-3:
Rush and Fosmer, (2014); FERM-4: Van De Graaf, Vallianpoer, Fiey, Delattre and Schulten,
(2012); FERM-5: Vemuri et al., 2002; FERM-6: Guettler, Jain and Rumler, (1996); FERM-7: Lee et
al., 2008; FERM-8: & FERM-9: Schroder, Haefner, Abendroth, Hollmann, Raddatz, Ernst and
Gurski, (2014); FERM-10: S. Y. lee, J. W. Lee, Choi and Yi, (2014))
Organism Strain name Ferm Type Carbon
source
Titer
(g/l)
Yield
(g/g)
Productivity
(g/l/h)
Broth
pH
FERM-1 Bacteria A. succinoproducens
ATCC 53488 Batch Glucose 43.5 0.87 1.93 6.10
FERM-2 Bacteria A. succinoproducens
ATCC 53488 Batch Glucose 30.8 0.90 1.10 6.20
FERM-3 Yeast I. orientalis,
13723 Batch Glucose 48.2 0.45 0.97 3.00
FERM-4 Yeast S. cerevisiae,
SUC-297 Fed-batch Glucose 43.0 0.31 0.45 3.00
FERM-5 Bacteria E. coli,
AFP111/pTrc99A- pyc Fed-batch Glucose 99.2 1.10 1.30 6.80
FERM-6 Bacteria A. succinogen, FZ53 Batch Glucose 105.8 0.83 1.36 6.08
FERM-7 Bacteria M. succiniciproducens
LPK7 Fed-batch Glucose 52.4 0.76 1.80 6.50
FERM-8 Bacteria B. succiniciproducens
DD1 Batch Glycerol 36.2 1.26 1.51 6.50
FERM-9 Bacteria B. succiniciproducens
LU 15224 Batch
Glycerol +
Maltose 69.8 1.11 2.91 6.50
FERM-10 Bacteria M. succiniciproducens
PALFK Fed-batch
Sucrose +
Glycerol 78.4 1.07 6.03 6.50
Page 144
Case Studies
124
Generation of base case flowsheet
There are numerous approaches that can be applied to identify the optimal processing route for
example, literature search, mathematical optimization based approach or ProCAFD (Tula et al.,
2017). Here, the superstructure based mathematical optimization approach has been applied.
Superstructure based process synthesis is an effective way to determine the optimal pathway
from a network of alternatives. This is because using a mathematical optimization approach for
a superstructure, a large number of processing routes as possible alternatives in terms of
processing steps and processing intervals can be generated. It is based on an integrated
framework for synthesis and design of processing networks (Quaglia et al., 2013). The processing
steps are defined as number of steps required to achieve the final result while processing intervals
are defined as alternatives within the processing step. This kind of superstructure representation
has been termed as “Processing Step-Interval Network (PSIN)” (Bertran et al., 2017).
To generate a superstructure, the basic fermentation data is collected as shown in Table 6.16.
Further, there are different purification techniques or technologies available in literature to
obtain succinic acid of a given purity. In principle, the minimum number of separation steps
required to separate N components is N - 1. This is the minimum to separate all the compounds
individually. But, in this case study the main objective is to produce pure succinic acid. Thus, the
logical rules are also followed, for example after fermentation step, the biomass is removed first,
and by-products present in low amount are not recovered.
Many of the various processing steps and intervals are thus identified based on available data
and current technologies reported in the scientific literature (Table 6.17). The superstructure is
set up in Super-O which is an interface to formulate and solve superstructure-based optimization
problems (Bertran et al., 2017). The optimization problem is solved by using solvers from an
external software GAMS (GAMS Development Corporation, 2012), where Super-O is a user
interface to enter required data and information. Processing interval information on raw
materials, main products, side products, reactions, chemical added, utilities and economic data
such as product price, raw material cost and chemical cost has been collected from patents,
published articles and scientific reports, available industrial data and databases. Every interval
in the PSIN representation of the superstructure is modelled with the same set of generic
equations representing a sequence of processing tasks, namely mixing, reaction, waste removal
and product separation, as well as utility consumption. Multiple inlets to and outlets from the
interval are allowed, including recycle streams from downstream intervals and bypasses.
A representation of the generic model is shown in Figure 6.29. Here, “f” represents the
component flow rates at different positions for different parameters while “g” denotes the flow
rate of added/removed component/utility. Further details regarding setting up the problem,
generic mathematical model and entering the required data in Super-O can be read in detail in
article by Bertran et al. (2017).
Page 145
6.3. Case study 3: Production of Bio-Succinic Acid
125
Table 6.17: Processing steps and processing intervals for superstructure
Processing Interval Reference
I. Raw Material
GLU Glucose -
GLY Glycerol -
MAL Maltose -
SUC Sucrose -
II. Fermentation
FERM 1 Fermentation option 1 using bacterial strain and Glucose Datta et al., 1992
FERM 2 Fermentation option 2 using bacterial strain and Glucose Glassner and Datta, 1992
FERM 3 Fermentation option 3 using yeast strain and Glucose Rush and Fosmer, 2014
FERM 4 Fermentation option 4 using yeast strain and Glucose Van De Graaf et al. 2012
FERM 5 Fermentation option 5 using bacterial strain and Glucose Vemuri et al., 2002
FERM 6 Fermentation option 6 using bacterial strain and Glucose Guettler et al., 1996
FERM 7 Fermentation option 7 using bacterial strain and Glucose Lee et al., 2008
FERM 8 Fermentation option 8 using bacterial strain and Glycerol Schroder et al., 2014
FERM 9 Fermentation option 9 using bacterial strain and Glycerol + Maltose Schroder et al., 2014
FERM 10 Fermentation option 10 using bacterial strain and Sucrose + Glycerol Lee et al., 2014
III. Biomass Removal
BIOR-MFLT Biomass removal using microfiltration Vogel and Todaro, 1996; Hong et al., 2009; Soper et al., 2013
BIOR-ULFT Biomass removal using ultrafiltration
BIOR-CENT Biomass removal using centrifugation
IV. Concentration Pre-Isolation
CPRI-DSTL Concentrating the broth using distillation Bernier et al., 2013
CPRI-EVAP Concentrating the broth using evaporation Gerberding et al., 2012
CPRI-EXTR Concentrating the broth using extraction King and Poole, 1995
CPRI-PVAP Concentrating the broth using pervaporation Van Baelen et al., 2005
BYPASS Concentration pre-isolation step is bypassed -
V. Isolation
SEP-CSSP Isolation of succinic acid from succinate salt containing calcium Datta et al., 1992
SEP-IEXC Isolation of succinic acid from succinate salt using ion-exchange Gerberding et al., 2012
SEP-SUSP Isolation of succinic acid from succinate salt using methanol Yedur et al., 2001
SEP-REXT Isolation of succinic acid from succinate salt using reactive extraction Vaswani, 2010
SEP-EDLS Isolation of succinic acid from succinate salt using Electrodialysis Glassner and Datta, 1992
BYPASS Isolation step is bypassed -
Page 146
Case Studies
126
VI. Impurities Removal
IMPR-IEXC Removal of soluble impurities using Ion exchange Schroder et al., 2014
IMPR-CTRT Removal of soluble impurities using carbon treatment Choi et al., 2016
IMPR-NFLT Removal of soluble impurities using Nano-filtration Gerberding et al., 2012
BYPASS Impurities removal is bypassed -
VII. Concentration Post-Isolation
CPSI-DSTL Concentrating the broth using distillation Bernier et al., 2013
CPSI-EVAP Concentrating the broth using evaporation Gerberding et al., 2012
CPSI-EXTR Concentrating the broth using extraction King and Poole, 1995
CPSI-PVAP Concentrating the broth using pervaporation Van Baelen et al., 2005
BYPASS Concentration post-isolation step is bypassed -
VIII: Purification
PUR-ECRY Purification of succinic acid using evaporative crystallization Graaf et al., 2011
PUR-SCRY Purification of succinic acid using solvent crystallization Yedur et al., 2001
PUR-CCRY Purification of succinic acid using cooling crystallization Choi et al., 2016
IX. Drying
DRYING Purification of succinic acid by removing remaining impurities -
X. Product
SUC ACD Pharmaceutical grade succinic acid (>99 wt. %) -
Figure 6.29: Generic processing interval scheme (Bertran et al., 2017)
The economic data for product price, raw material costs, chemical costs and utility costs (Tan et
al., 2017; Biorefinery database (Bertran et al., 2017); ICIS price reports, (2016); Ycharts, (2014);
Page 147
6.3. Case study 3: Production of Bio-Succinic Acid
127
Costs of doing business in Thailand, (2014); Intratec utility pricing, (2016); Industrial Price
Comparison - Rocky Mountain Power, (2018); Harrison, Todd P, Todd PW, Rudge, Petrides,
(2015)) is given in Appendix G.1.
The superstructure optimization is performed for 3 different scenarios based on location and
objective function. Overall objective remains same for all the scenarios which is to maximize the
profit. The 3 different scenarios are explained as follows:
• Scenario 1: The plant location is set to USA and the objective function is based upon
sales of product
• Scenario 2: The plant location is same as scenario 1 i.e. USA, but an additional effect of
operating cost is added to the objective function
• Scenario 3: Same as scenario 2 except the plant location has been changed to Thailand
The superstructure describing the network of configurations for different processing routes has
8 processing steps and 33 processing intervals excluding raw material and product steps. The
PSIN representation of alternatives containing the processing intervals, raw materials and
products is shown in Figure 6.30.
An optimization problem is solved for each scenario using the same generic model. The statistics
of the optimization problem for bio succinic acid is shown in Table 6.18.
Table 6.18: Statistics for the optimization problem for bio succinic acid production
Superstructure
No. of feed (NF) 4
No. of product (NP) 1
No. of processing steps (NS) 8
No. of intervals NI (excluding NF and NP) 33
Model and Solver
No. of equations (NEQ) 989,003
No. of variables (NV) 973,451
No. of discrete variables (NDV) 164
Problem type MILP
Solver CPLEX
The results in terms of objective function for 3 different scenarios is shown in Table 6.19 and
optimal topology is shown in Figure 6.30 denoted with different colors. It is observed that, the
optimal topology for scenario 1 and 2 is coming out to be the same, while in scenario 3, the raw
material and the fermentation has changed owing to one of the major reasons being lower prices
of Glycerol as compared to the Glucose. The objective function depends on the product sales
(SPROD), raw material (CRAW), chemical (CC) and utility (CU) costs (scenario 2 and 3).
Page 148
Cas
e S
tud
ies
12
8
Fig
ure
6.3
0:
Su
pe
rstr
uct
ure
sh
ow
ing
th
e n
etw
ork
of
pro
cess
ing
ro
ute
s to
pro
du
ce b
io s
ucc
inic
aci
d f
rom
dif
fere
nt
raw
m
ate
ria
ls i
ncl
ud
ing
ca
rbo
n d
iox
ide
(a
lso
sh
ow
n i
de
nti
fie
d e
xis
tin
g r
ou
tes
an
d o
pti
ma
l ro
ute
s fo
r 3
dif
fere
nt
sce
na
rio
s)
FE
RM
1
FE
RM
2
FE
RM
3
FE
RM
4
FE
RM
5
FE
RM
6
FE
RM
7
FE
RM
8
FE
RM
9
FE
RM
10
BIO
R-
MF
LT
BIO
R-
UF
LT
BIO
R-
CE
NT
CP
RI-
DS
TL
CP
RI-
EV
AP
CP
RI-
EX
TR
CP
RI-
PV
AP
BY
PA
SS
SE
P-
CS
SP
SE
P-
IEX
C
SE
P-
SU
SP
SE
P-
RE
XT
SE
P-
ED
LS
BY
PA
SS
IMP
R-
IEX
C
IMP
R-
CT
RT
IMP
R-
NF
LT
BY
PA
SS
CP
SI-
DS
TL
CP
SI-
EV
AP
CP
SI-
EX
TR
CP
SI-
PV
AP
BY
PA
SS
PU
R-
EC
RY
PU
R-
SC
RY
PU
R-
CC
RY
DR
YIN
G
Ra
w
Mate
ria
lF
erm
en
tati
on
Bio
ma
ss
Rem
oval
Co
nce
ntr
ati
on
Pre-i
sola
tion
Isola
tion
Imp
urit
ies
Rem
ov
al
Con
cen
trati
on
Post
-iso
lati
on
Pu
rif
icati
on
Dry
ing
Prod
uct
GL
U
MA
L
SU
C
GL
Y
SU
C
AC
D
531
Exis
tin
g
alt
ern
ati
ves
Scen
ario
1 &
2
Scen
ario
32 4
Page 149
6.3. Case study 3: Production of Bio-Succinic Acid
129
The sensitivity analysis on the variation of prices is also performed. From this analysis, ±10%
fluctuation in the product price brings ±14.3 to ±18.3% change in the objective function for all
the scenarios. Similarly, a ±10% fluctuation in the raw material and utility prices brings ±1.3 to
±3.2% and ±0.7 to ±1.2% changes respectively, in the objective function for all the scenarios. In
all the above cases, the optimal processing route (flowsheet) remains unchanged. The optimal
processing route identified for different scenarios is as follows:
• Scenario 1: GLU → FERM 5 → BIOR-CENT → CPRI-DSTL → BYPASS → IMPR-CTRT →
BYPASS → PUR-CCRY → DRYING → SUC ACD
• Scenario 2: GLU → FERM 5 → BIOR-CENT → CPRI-DSTL → BYPASS → IMPR-CTRT →
BYPASS → PUR-CCRY → DRYING → SUC ACD
• Scenario 3: GLY+MAL → FERM 9 → BIOR-CENT → CPRI-DSTL → BYPASS → IMPR-
CTRT → BYPASS → PUR-CCRY → DRYING → SUC ACD
Table 6.19: Results of the superstructure based mathematical optimization
Scenario 1 Scenario 2 Scenario 3
Location USA USA Thailand
Objective function SPROD - CRAW - CC SPROD - CRAW - CC - CU SPROD - CRAW - CC - CU
Total product sale (M$/y) 70.02 70.02 70.02
Raw material cost (M$/y) 12.19 12.19 6.44
Chemicals cost (M$/y) 15.27 15.27 12.66
Utilities cost (M$/y) - 4.33 2.31
Execution time (seconds) 2.50 2.52 2.56
Objective function (M$/y) 42.56 38.23 48.61
The optimal processing routes identified for all 3 different scenarios are novel processing routes.
Also, as shown in Figure 6.30, along with optimal processing routes, 5 other existing routes in
literature are also identified. These existing routes are denoted with different colors in the PSIN
representation.
• Existing alternative 1 (Datta, Glassner, Jain and Roy, 1992): GLU → FERM 1 → BIOR-
MFLT→ BYPASS → SEP-CSSP → BYPASS → CPSI-EVAP→ PUR-ECRY → DRYING →
SUC ACD
• Existing alternative 2 (Glassner and Datta, 1992): GLU → FERM 2 → BIOR-MFLT→
BYPASS → SEP-EDLS→ BYPASS → BYPASS→ PUR-CCRY → DRYING → SUC ACD
• Existing alternative 3 (Van De Graaf, Vallianpoer, Fiey, Delattre and Schulten,
2012): GLU → FERM 4 → BIOR-MFLT→ BYPASS → SEP-IEXC → BYPASS → CPSI-
EVAP→ PUR-ECRY → DRYING → SUC ACD
Page 150
Case Studies
130
• Existing alternative 4 (Vaswani, 2010): GLU → FERM 7 → BIOR-UFLT→ BYPASS →
SEP-REXT → BYPASS → CPSI-DSTL→ PUR-CCRY → DRYING → SUC ACD
• Existing alternative 5 (Schroder, Haefner, Abendroth, Hollmann, Raddatz, Ernst
and Gurski, 2014): GLY+MAL → FERM 9 → BIOR-MFLT→ BYPASS → SEP-IEXC→
BYPASS → CPSI-EVAP→ PUR-CCRY → DRYING → SUC ACD
The optimal processing route from scenario 1 and 2 is considered for further analysis in stage 2
and 3. The process flowsheet for the selected alternative (base case flowsheet) is shown in Figure
6.31. The first step is fermentation where non-condensable gases are removed from the top of
fermenter followed by microfiltration to separate the biomass from the culture broth. Then the
cell free broth is distilled in order to concentrate the solution and facilitate crystallization. The
color of the culture broth caused by certain impurities is removed by activated carbon treatment.
Then the feed is sent to crystallizer where cooling crystallization is performed by lowering the
pH followed by drying of the pure succinic acid crystals to remove any remaining water or
impurities.
Figure 6.31: Process flowsheet of selected alternative for bio-succinic acid
Base case design and analysis
The base case is rigorously simulated using PRO/IITM and the UNIQUAC model is used for the
liquid activity coefficients. Optimized UNIQUAC parameters for the calculation of water-acetic
acid VLE system is retrieved from Pirola et al. (2014). The solubility of succinic acid in water is
shown in solubility curve in Figure 6.32 (Sundaram, 2015). The recovery of succinic acid at a
particular temperature is determined using this curve. Then, the detailed mass and energy
balance data along with number of streams, unit operations data is extracted to carry out analysis
in the next step. An overview of the key simulation results is given in Table 6.20.
FERMENTATIONBIOMASS
REMOVALRECOVERY AND PURIFICATION
OP 06
OP 22
Fermentation
Biomass
Water, Acetic acid, EthanolNon cond gases
Glucose, Water,
Sol. solids
Carbon dioxide Water
Succinic Acid crystals
Waste waterCentrifugation
DistillationActivated carbon
treatment
Act. carbon
Crystallization
Drying
Spent carbon,
Sol. solids
Page 151
6.3. Case study 3: Production of Bio-Succinic Acid
131
Figure 6.32: Solubility curve for succinic acid in water (Sundaram, 2015)
Table 6.20: Key results from rigorous simulation of Base case
Parameter Value
Succinic acid product (kg/h) 3750.40
Succinic acid purity (wt. %) > 99
Total energy supplied (MJ/h) 73240.53
Total energy withdrawn (MJ/h) 68875.03
Further, the detailed analysis in terms of process economics, sustainability and life cycle
assessment is performed. In house tools ECON, SustainPro and LCSoft are used to carry out the
respective analysis. The main results from sustainability analysis performed using SustainPro are
shown in Table 6.21. In Figure 6.31, the most critical open paths (OP) identified for potential
improvements are highlighted.
Table 6.21: List of critical paths with highest potential for improvement (MVA-Material vale added, EWC-Energy and waste cost, TVA-Total value added)
Path Compound Flowrate MVA EWC TVA
kg/hr 103 $/yr 103 $/yr 103 $/yr
OP 06 Water 19508.4 - 449.4 -
OP 22 Succinic acid 662.4 -1493.1 611.0 -2104.0
In OP 06, which follows the compound water is present in excess in the system has a high energy
waste cost (EWC). The unit operation mainly belonging to this path is distillation column. This
translates to loss of energy in the open path and thus potential to recover or reduce energy
consumption during distillation operation whose objective is to remove unwanted byproducts
0
100
200
300
400
500
600
700
800
900
1000
1100
0 10 20 30 40 50 60 70 80 90 100 110 120 130
So
lub
ilit
y (
g/l
of
wa
ter)
Temperature (OC)
Page 152
Case Studies
132
(ethanol and acetic acid) and concentrate the broth. OP 22 follows the main product succinic
acid path ending at crystallizer outlet and has high negative value of MVA and positive value of
TVA. This translates to loss of product and potential for improvement in recovery of product.
As can be seen in Figure 6.33 a), LCA analysis (using LCSoft) shows that the carbon footprint is
highest for the reboiler of the distillation column and as expected, economic analysis performed
using ECON (Figure 6.33 b)) shows that the utility cost is highest for the same reboiler.
Figure 6.33: a) LCA analysis (carbon footprint); b) Utility cost distribution
6.3.2. Application of extended phenomena based synthesis method
This section present results for the application of extended phenomena-based synthesis method
on bio-succinic acid. This extended method is developed by Garg et al. (2019) which is based on
the previous work from Babi et al. (2015) and Lutze et al. (2013). A brief introduction of these
methodologies and extensions are given in chapter 1.
The extended framework (Garg et al., 2019) consists of 3 steps, where in first step, existing process
flowsheet is translated to task and phenomena based flowsheet followed by generation of
intensified flowsheet alternatives. The generated alternatives are then analyzed and screened
according to the pre-defined performance criteria. Application of these steps on the optimal
process flowsheet identified for bio-succinic acid generates 3 intensified flowsheet alternatives.
The task based superstructure showing the base case and alternatives is shown in Figure 6.34.
Three intensified flowsheet alternatives are explained as follows:
• Flowsheet alternative 1: The merging of reaction and separation tasks is considered to
perform these two tasks simultaneously. Thus, in this alternative, starting with the first
task of reaction, the second task, cell removal or clarification of broth are combined. The
task based flowsheet for alternative 1 is highlighted with blue color in Figure 6.34. The
task based flowsheet is translated to unit operation based flowsheet where, the combined
reaction and separation task are translated to membrane reactor (bio). In this unit
0
1
2
3
4
Car
bo
n f
oo
tpri
nt,
CO
2e
q.
EquipmentUnit Operation
Comp. HEX (Hot Utl.) HEX (Cold Utl.) T1-cond T1-reb
0
15
30
45
60
75
Uu
tilit
y co
st, %
EquipmentUnit Operation
Comp. HEX (Hot Utl.) HEX (Cold Utl.) T1-cond T1-reb
Page 153
6.3. Case study 3: Production of Bio-Succinic Acid
133
operation, the fermentation broth is clarified i.e. the reaction product is removed
continuously and the cell culture remains in the membrane bioreactor leading to
increased cell concentration and product yield, which is also observed by Wang et al.
(2014). According to Wang et al. (2014), using membrane based fermentation and
separation system the problem of succinic acid inhibition is alleviated by removing acids
and thus yielding better results. The unit operation based flowsheet for alternative 1 is
shown in Figure 6.35.
(A – Oxygen, B – Carbon dioxide, C – Ammonia, D – Ethanol, E – Water, F – Acetic acid, G –
Succinic acid, H- Glucose, I – Soluble solids, J – Biomass)
Figure 6.34: Task based superstructure for the production of bio-succinic acid
• Flowsheet alternative 2: In this alternative again, the merging of tasks is considered for
the last two separation tasks and is found to be feasible as both the separation tasks share
the similar set of phenomena with liquid-solid phase. Therefore, merging of S-Task 4 and
S-Task 5 (Figure 6.36) is done to generate a new feasible combination. Here, performance
R-Task 1 S-Task 1 S-Task 2 S-Task 3 S-Task 4 S-Task 5 S-Task 6
React. Sep.. J(DEFGHI) Sep.. D(EFGHI) Sep. E(FGHI) Sep. F(GHI) Sep. G(HI) Sep. H(I)
Sep.. E(DFGHI) Sep. D(FGHI) Sep. D(EHI) Sep. E(HI) Sep. E(I)
React.+Sep.
J(DEFGH)ISep.. F(DEGHI) Sep. G(DEHI) Sep. G(HI) Sep. H(GI) Sep. G(I)
React.+Sep.
J(DEFG)HISep. G(DEFHI) Sep. F(DEHI) Sep. E(HI) Sep. H(EI) Sep. …………….
React.+Sep.
J(DEF)GHISep. DE(FGHI) Sep. ……………. Sep. …………… Sep. GH(I)
React.+Sep.
J(DE)FGHISep. DEF(GHI) Sep. EF(GHI) Sep. EH(I)
React.+Sep.
J(DE)FGHISep. DEFG(HI) Sep. DF(GHI) Sep. FGH(I) Sep. …………….
React.+Sep.
J(D)EFGHISep. DEFGH(I) Sep. GD(EHI) Sep. …………….
React.+Sep.
…………….Sep. EF(DGHI) Sep. FD(EHI) Sep. H(I) Sep. …………….
Sep. …………… Sep. ……………. Sep. …………….
Base case Sep. DF(EGHI) Sep. EFG(HI)
Alternative 1 Sep. ……………. Sep. DFG(HI) Sep.. F(G)
Alternative 2 Sep.. D(EFGH) Sep. ……………. Sep. …………….
Alternative 3 Sep.. D(EFG) Sep.. E(FGH)
Sep. ……………. Sep.. E(FG)
Sep. …………….
React.
React.+Sep. (J)DEFGHI
Sep.. J(DEFGHI)
Sep. DF(EGHI)
Sep. I(EGH)
Sep.. G(EH)
Sep.. EG(EH)
Sep.. G(E)
Page 154
Case Studies
134
of the task is enhanced by PS(LL) PBB from the list of phenomena. The task based
flowsheet for alternative 2 is highlighted purple color in Figure 6.34. The combination of
separation tasks is then translated to membrane crystallizer using a reverse osmosis
membrane (Kuhn et al., 2009). Kuhn et al. (2009) showed that the crystallization
performance of organic acids can be significantly improved using RO membranes. The
corresponding unit operation based flowsheet for this alternative is shown in Figure 6.36.
• Flowsheet alternative 3: This alternative is combination of alternative 1 and 2, where
combination of reaction and adjacent separation task, two last separation task is
considered to generate new feasible alternatives. The task based flowsheet is highlighted
with red color in Figure 6.34 and corresponding unit-operation based flowsheet is shown
in Figure 6.37.
Figure 6.35: Alternative 1 generated using extended phenomena based synthesis
Figure 6.36: Alternative 2 generated using extended phenomena based synthesis
Fermentation
Water, Acetic acid, EthanolNon cond gases
Glucose, Water,
Sol. solids
Carbon dioxide Water
Succinic Acid crystals
Waste water
DistillationActivated carbon
treatment
Act. carbon
Crystallization
Drying
Spent carbon,
Sol. solids
Membrane
bio-reactor
Fermentation
Biomass
Water, Acetic acid, EthanolNon cond gases
Glucose, Water,
Sol. solids
Carbon dioxide
Succinic Acid
crystals
Waste water
Centrifugation
DistillationActivated carbon
treatment
Act. carbon
Membrane
Crystallization
Spent carbon,
Sol. solids
Page 155
6.3. Case study 3: Production of Bio-Succinic Acid
135
Figure 6.37: Alternative 3 generated using extended phenomena based synthesis
6.3.3. Framework application
Stage I: Synthesis analysis
• Step 1: Problem definition
The synthesis problem definition is to produce bio-succinic acid from glucose and carbon
dioxide with a purity of at least 99 wt. %. The target annual production of bio-succinic
acid is set to be same as section 6.3.1 i.e. 30 kt/y.
- S1.1. Problem type
The problem type identified is indirect synthesis as the flowsheet synthesized in
section 6.3.1 is considered as the base case for this application.
- S1.2. Information collection
The optimal processing route from section 6.3.1 consists of fermentation pathway
from Vemuri et al. (2002). The fermentation operates at 37 OC and normal pressure.
The fermentation feed (similar to the base case) consists of glucose and CO2 along
with other necessary components and nutrients. The fermentation reaction in
presence of E. coli, AFP111/pTrc99A- pyc strain does not go to full completion i.e. all
main raw material does not get consumed; therefore, the fermenter outlet contains a
mixture of raw materials, products and byproducts.
• Step 2: Problem analysis
- S2.1. Reaction analysis
The fermentation reaction takes place at moderate conditions where the yield of main
product, succinic acid is 1.1 g/g of glucose (main raw material). The concentration of
the product at the outlet is 99.2 g/l with a productivity of 1.3 g/l/h. The strain used
for fermentation is E. coli, AFP111/pTrc99A- pyc. The fermentation releases energy
thus, is slightly exothermic in nature.
Fermentation
Water, Acetic acid, EthanolNon cond gases
Glucose, Water,
Sol. solids
Carbon dioxide
Succinic Acid
crystals
Waste water
DistillationActivated carbon
treatment
Act. carbon
Membrane
Crystallization
Spent carbon,
Sol. solids
Membrane
bio-reactor
Page 156
Case Studies
136
- S2.2. Mixture analysis
The outlet of the fermenter consists of several components that are categorized
further for the simplification of the problem. The outlet of fermenter includes
product succinic acid, biomass, impurities in form of soluble solids, water, unreacted
raw material i.e. glucose, by products ethanol and acetic acid. The key components
considered for the mixture analysis are succinic acid, water, acetic acid and ethanol.
The components present in the system are annotated as: A – Oxygen, B – Carbon
dioxide, C – Ammonia, D – Ethanol, E – Water, F – Acetic acid, G – Succinic acid, H-
Glucose, I – Soluble solids, J – Biomass.
Pure component analysis
The list of pure component properties for selected components is retrieved from
ICAS database (Gani et al. 1997; Gani 2002) and literature search. The retrieved
list is shown in Table 6.22. The binary ratio matrix generated for selected set of
pure component properties is shown in Table 6.23.
Table 6.22: Pure component properties data for compounds involved in the problem
Property UOM Oxygen
(A) Carbon
dioxide (B) Ammonia
(C) Ethanol
(D) Water
(E) Acetic
acid (F) Succinic acid (G)
MW (g/mol) 31.99 44.01 17.031 46.069 18.02 60.05 118.09
ω - 0.02 0.22 0.25 0.65 0.3449 0.47 0.99
Tc (K) 154.58 304.21 405.65 513.92 647.13 591.95 806.00
Pc (atm) 49.77 72.86 111.33 60.68 217.67 57.10 46.48
Zc - 0.29 0.27 0.24 0.24 0.229 0.211 0.22
Vc (m3/kmol) 0.07 0.09 0.07 0.2 0.1 0.17 0.32
Tb (K) 90.19 194.7 239.72 351.44 373.15 391.05 591.00
dm (Debye) 0.00 0.00 1.47 1.69 1.84 1.74 2.20
rg (Å) 0.68 1.04 0.85 2.26 0.62 2.61 4.16
Tm (K) 54.36 216.58 195.41 159.05 273.15 289.81 460.65
Ttp (K) 54.36 216.58 195.41 159.05 273.16 289.81 460.65
Ptp (atm) 1.5E-03 5.12 0.06 4.8E-09 6.03E-03 1.2E-02 8.7E-03
Hf (kJ/kmol) 0.00 -3.93E+05 -4.5E+04 2.3E+05 -2.4E+05 -4.3E+05 -8.2E+05
Gf (kJ/kmol) 0.00 -3.94E+05 -1.6E+04 1.6E+05 -2.2E+05 -3.8E+05 -6.9E-05
SIG (kJ/kmol·K) 205.04 213.68 192.66 281 1.8E+02 2.8E+02 403.4
Hfus (kJ/kmol) 4.4E+02 9.01E+03 5657 4930 6.0E+03 1.1E+04 5.3E+04
Hcomb (kJ/kmol) 0.00 0.00 -3.1E+05 -1.2E+06 0.00 -8.2E+05 -1.3E+06
δ (√kJ/m3) 8.18 14.56 29.23 26.13 47.81 19.01 29.34
Vvw (m3/kmol) 0.013 0.02 0.014 0.03 0.012 0.03 0.06
Avw (m2/kmol) 2.3E+08 3.2E+08 2.4E+08 4.9E+08 2.2E+08 5.1E+08 8.8E+08
Pvap (Pa) 4.3E+07 5.7E+06 8.6E+05 7.9E+03 3.1E+03 2.0E+03 1.5E-05
Page 157
6.3. Case study 3: Production of Bio-Succinic Acid
137
Table 6.23: Binary ratio matrix for the selected set of properties
Binary pair/Property Tb Tm δ Vvw rg MW
Oxygen (A)
Carbon dioxide (B)
2.16 3.98 1.78 1.52 1.53 1.38
Ammonia (C)
2.66 3.59 3.57 1.06 1.25 1.88
Water (E)
4.14 5.02 5.84 1.05 1.11 1.78
Ethanol (D)
3.90 2.93 3.19 2.45 3.32 1.44
Acetic Acid (F)
4.34 5.33 2.32 2.56 3.84 1.88
Succinic Acid (G)
6.55 8.47 3.59 4.58 6.12 3.69
Carbon dioxide (B)
Ammonia (C)
1.23 1.11 2.01 1.43 1.22 2.58
Water (E)
1.92 1.26 3.28 1.59 1.69 2.44
Ethanol (D)
1.81 1.36 1.79 1.62 2.17 1.05
Acetic Acid (F)
2.01 1.34 1.31 1.69 2.51 1.36
Succinic Acid (G)
3.04 2.13 2.01 3.02 4.00 2.68
Ammonia (C)
Water (E)
1.56 1.40 1.64 1.12 1.39 1.06
Ethanol (D)
1.47 1.23 1.12 2.31 2.65 2.71
Acetic Acid (F)
1.63 1.48 1.54 2.41 3.06 3.53
Succinic Acid (G)
2.47 2.36 1.00 4.31 4.88 6.93
Water (E)
Ethanol (D)
1.06 1.72 1.83 2.58 3.67 2.56
Acetic Acid (F)
1.05 1.06 2.52 2.69 4.24 3.33
Succinic Acid (G)
1.58 1.69 1.63 4.81 6.76 6.56
Ethanol (D)
Acetic Acid (F)
1.11 1.82 1.37 1.04 1.16 1.30
Succinic Acid (G)
1.68 2.90 1.12 1.87 1.84 2.56
Acetic Acid (F)
Succinic Acid (G)
1.51 1.59 1.54 1.79 1.59 1.97
Mixture property analysis
Non condensable gases as in the base case are considered to be removed from
fermenter itself. Further, insoluble solids like biomass are removed immediately
after the fermenter. Further, following analysis is performed for the mixture from
the reactor outlet:
▪ The mixture state or phase (after fermentation) – Liquid
Page 158
Case Studies
138
▪ State of pure components (fermentation outlet) at the mixture conditions
and ambient conditions.
- Mixture conditions: Ethanol, Water, Acetic acid, Succinic acid - Liquid
- Ambient conditions
Ethanol, Water, Acetic acid – Liquid, Succinic acid - Solid
▪ Azeotrope – Water and ethanol
▪ Liquid-liquid phase splits or eutectic points – None
Additionally, it has also been identified that acetic acid and water system does
not make an azeotrope at normal conditions but shows a tangent pinch at water
side (Pirola et al., 2014) as shown in the Appendix G.2. Thus, the separation of
this mixture using simple distillation technique to recover pure components is
not technically feasible. Also, succinic acid is highly soluble in water as shown in
Figure 6.32 and solubility increases with increase in temperature.
Stage II: Base case analysis
The objective of stage II is to analyze the selected base case synthesized in section 6.3.1. The base
case flowsheet for production of bio succinic acid shown in Figure 6.31.
• Step 3: Generation of task and phenomena based flowsheet
- S3.1. Task based flowsheet
The base case flowsheet shown in Figure 6.31 is translated to task based flowsheet by
identifying unit-operations involved in the process. The unit-operations involved are
fermenter, filtration, distillation column, adsorption column, crystallizer and dryer.
The task based flowsheet is shown in Figure 6.38.
Figure 6.38: Task based flowsheet for the base case
- S3.2. Phenomena based flowsheet
The phenomena based flowsheet is shown in Figure 6.39. An initial list of phenomena
obtained from the phenomena-based flowsheet consists of following PBBs: M, 2phM,
R(L), ES(C), ES(H), PC(VL), PC(LS), PT(VL), PT(LS), PS(VL), PS(LS).
Reaction task
Glucose + Water
CO2
Spent C + Soluble solids
EtOH+Water+AcA
Biomass
Separation task Separation task
Separation task
Non-Condensable gases
Glucose+Water+Succinic Acid+
Acetic acid
Separation task
Water
Separation task
Succinic Acid
Act. carbon
Page 159
6.3. Case study 3: Production of Bio-Succinic Acid
139
Figure 6.39: Phenomena based flowsheet for the base case
• Step 4: Identification of additional task and phenomena
- S4.1. Process hotspots and design targets
The process hotspots are identified based on economic, sustainability and life cycle
analysis in section 6.3.1. Further using the Appendix B, following design targets are
desired:
o Reduce energy consumption
o Reduce utility cost
o Improvement in LCA/sustainability indictors
o Unit operation reduction
o Product purity (to be kept at least as base case)
o Production target (to be kept at least as base case)
o Waste minimization
- S4.2. Additional task and phenomena
A list of additional task and phenomena are identified based on the process hotspots
using algorithm A2.3 and knowledge base KB2.2. These are shown in Table 6.24.
Table 6.24: Additional task and phenomena to overcome identified process hotspots
Process Hotspot
Main task Binary
pair
Pair or Reaction
phase
Alternative Task
MSA Principle PBBs
High energy consumption/demand
Separation E/G L Separation Y PC(LL), PT(LL), PS(LL)
Separation E/G L Separation Y PC(LS), PS(LS)
Separation E/G L Separation Y 2phM, PC(VL), PT(VL), PS(VL), ES(C). ES(H)
Separation E/G L Separation N 2phM, PC(VL), PT(VL), PS(VL), ES(C). ES(H)
Separation E/G L Separation N PT(MVL), PS(VL)
Separation E/G L Separation N PT(MLL), PS(LL)
M, 2phM, R(L)
Glucose + Water
CO2
Spent C + Soluble solids
EtOH+Water+AcA
Biomass
M, PC(LS), PS(LS)M, 2phM, ES(C),
ES(H), PC(VL), PT(VL), PS(VL)
M, PC(LS), PS(LS)
Non-Condensable gases
Glucose+Water+Succinic Acid+
Acetic acid
M, ES(C), PC(LS), PT(LS)
Water
M, ES(H), PT(VL), PS(VL)
Succinic Acid
Act. carbon
Page 160
Case Studies
140
Stage III: Generation of feasible flowsheet alternatives
• Step 5: Generation of mathematical combinatorial superstructure of compounds
The mathematical combinatorial superstructure of compounds is generated by following
algorithm A3.1. Compounds like oxygen, unreacted carbon dioxide and ammonia are
non-condensable gases that are removed from fermenter only and thus are not
considered for the mathematical combinatorial superstructure. Raw materials must react
in presence of bacteria for a fermentation to take place and produce products, thus the
first task is the reaction task. The first separation task after fermentation is generally
broth clarification in bio processes i.e. biomass removal. So, to avoid any separation
problems, the first separation task is fixed as biomass (J) removal. Also, the impurities as
soluble solids are considered to be removed after mass removal. Glucose is present as a
solution in water and is considered to be removed along with water. Thus, based on these
considerations, the mathematical combinatorial superstructure is generated as shown in
Figure 6.40. The number of possible flowsheet alternatives at this step are 1080.
• Step 6: Identification of principle PBBs
The binary ratio matrix is retrieved from step 2 and thus following the algorithm A3.2,
principle PBBs for all the binary pairs are identified using knowledge base KB3.1 and are
listed in Table 6.25. The PBBs that are not feasible as per mixture phase at ambient or
reaction conditions are removed.
Table 6.25: Identified list of principle PBBs
Binary
pair
C + A → D + B, 2D → E + A
(---ABCDE---)
Ethanol/Water
(D/E)
Ethanol/Acetic acid
(D/F)
Ethanol/Succinic acid
(D/G)
Principle
PBBs
2phM, R(L) PT(MVL), PS(VL) 2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H) PT(MVL), PS(VL)
PT(MLL), PS(LL) PT(LS), PS(LS), ES(C/H) PT(MLL), PS(LL)
PT(LS), PS(LS), ES(C/H) PT(VL), PS(VL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
Binary
pair
Water/Acetic acid
(E/F)
Water/Succinic acid
(E/G)
Acetic acid/Succinic
acid (F/G)
Principle
PBBs
PT(MVL), PS(VL) PT(MVL), PS(VL) PT(MVL), PS(VL)
PT(MLL), PS(LL) PT(MLL), PS(LL) PT(MLL), PS(LL)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
2phM, PC(VL), PT(VL),
PS(VL), ES(C), ES(H)
PT(VL), PS(VL) PT(VL), PS(VL)
PT(LS), PS(LS), ES(C/H) PT(LS), PS(LS), ES(C/H)
PC(LL), PT(LL), PS(LL)*
2phM, PC(VL), PT(VL),
PS(VL)*, ES(C). ES(H)
PC(LS), PS(LS)*
Page 161
6.3. Case study 3: Production of Bio-Succinic Acid
141
Figure 6.40: Mathematical combinatorial superstructure of compounds
Fermentation
--ABC/DEFGIJ--D/EFG
D/FEG
DE/GF
ED/FG
D/GEF
DE/FG
ED/GF
DF/EG
FD/GE
DG/EF
DF/GE
FD/EG
DG/FE
GD/EF
GD/FE
E/DFG
E/FGD
E/GDF
F/DEG
F/EGD
F/GED
G/DEF
G/EFD
G/FDE
E/FG
E/GF
F/EG
F/GE
G/EF
G/FE
D/FG
D/GF
F/DG
F/GD
G/DF
G/FD
D/EG
D/GE
E/DG
E/GD
G/DE
G/ED
D/EG
D/GE
E/DG
E/GD
G/DE
G/ED
F/G
E/G
E/F
D/G
D/F
D/E
F/G
E/G
D/G
D/E
E/G
D/G
D/E
F/G
D/F
E/G
D/G
F/E
DEFGI/J
Page 162
Case Studies
142
Ethanol and acetic acid are unwanted by products and are not considered for recovery as
pure components. Thus, being difficult separating binary, the phenomena for the same
are not considered. The phenomena for removal of I and J are kept same as the base case.
• Step 7: Generation of list of feasible SPBs
The list of feasible SPBs is generated using the PBBs identified in previous steps. The
total number of PBBs identified are M, 2phM, R(L), ES(C), ES(H), PC(VL), PC(LL),
PC(LS), PT(VL), PT(LS), PT(MVL), PT(MLL), PT(LL), PS(LL), PS(VL), PS(LS), D - 17.
- S7.1. Operating window for identified PBBs
The operating window of each phenomena is shown in Table 6.26.
Table 6.26: Operating window for all identified PBBs
Phenomena (PBB) Operating Window
M Tlow=159.05K (lowest melter)
Thigh=591.00K (highest boiler)
2phM Tlow=159.05K (lowest melter)
Thigh=591.00 (highest boiler)
R(L)
P= 40 bar (reaction pressure from literature)
Tlow=273.15K (lowest melter)
Thigh=310.15K (T for fermentation according to base case)
PC(VL) V-L present (also liquid separating agent)
PC(LL) L-L present (liquid separating agent)
PC(LS) L-S present (can be solid separating agent)
PT(VL) Tlow=351.35 K (lowest boiling azeotrope)
Thigh=591.00K (highest boiler)
PT(LS) Tlow=159.05K (lowest melter)
Thigh=460.65K (highest melter)
PT(MVL) Component affinity
PT(MLL) Component affinity
PS(LL) L-L present
PS(VL) V-L present
PS(LS) L-S present (can be solid separating agent)
PS(LL) L-L present (liquid separating agent)
ES(H) -
ES(C) -
D -
Page 163
6.3. Case study 3: Production of Bio-Succinic Acid
143
- S7.2. Feasible SPBs
The maximum number of SPBs including both feasible and infeasible are calculated
to be 26332 (from equation 4.2). The list of feasible SPBs generated from identified
PBBs using adjacency matrix and SPB building blocks is shown in Table 6.27. The
combination rules are applied together for principle PBBs with MSA’s.
Table 6.27: Generated list of feasible SPBs
SPB Connected PBB Task they may perform
SPB.1 M Mixing
SPB.2 M=2phM Mixing
SPB.3 M=R(L) Mixing+Reaction
SPB.4 M=ES(H) Mixing+Heating
SPB.5 M=ES(C) Mixing+Cooling
SPB.6 M=R(L)=ES(H) Mixing+Reaction+Heating
SPB.7 M=R(L)=ES(C) Mixing+Reaction+Cooling
SPB.8 M=2phM=R(L) Mixing+Reaction
SPB.9 M=2phM=ES(C) Mixing+Cooling
SPB.10 M=2phM=ES(H) Mixing+Heating
SPB.11 M=2phM=R(L)=ES(C) Mixing+Reaction+Cooling
SPB.12 M=2phM=R(L)=ES(H) Mixing+Reaction+Heating
SPB.13 M=2phM=PC(VL)=PT(VL) Mixing+ Phase creation
SPB.14 M=2phM=R(L)=PC(VL)=PT(VL) Mixing+Reaction+ Phase creation
SPB.15 M= 2phM=ES(C)=PC(VL)=PT(VL) Mixing+Cooling+ Phase creation
SPB.16 M= 2phM=ES(H)=PC(VL)=PT(VL) Mixing+Heating+ Phase creation
SPB.17 M=2phM=R(L)=ES(C)=PC(VL)=PT(VL) Mixing+Reaction+Cooling+ Phase creation
SPB.18 M=2phM=R(L)=ES(H)=PC(VL)=PT(VL) Mixing+Reaction+Heating+ Phase creation
SPB.19 M=PT(VL)=PS(VL) Mixing+Separation
SPB.20 M=R(V)=PT(VL)=PS(VL) Mixing+Reaction+Separation
SPB.21 M=ES(C)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.22 M=ES(H)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.23 M=R(L)=ES(H)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.24 M=R(L)=ES(C)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation
SPB.25 M=2phM=PC(VL)=PT(VL)=PS(VL) Mixing+Separation
SPB.26 M=2phM=ES(H)= PC(VL)=PT(VL)=PS(VL) Mixing+Heating+Separation
SPB.27 M=2phM=ES(C) =PC(VL)=PT(VL)=PS(VL) Mixing+Cooling+Separation
SPB.28 M=2phM=R(L)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Separation
SPB.29 M=2phM =R(L)=ES(H) =PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Heating+Separation
SPB.30 M=2phM=R(L)=ES(C)=PC(VL)=PT(VL)=PS(VL) Mixing+Reaction+Cooling+Separation
SPB.31 M=PT(MVL)=PS(VL) Mixing+Heating+Separation
SPB.32 M=PT(MLL)=PS(LL) Mixing+Cooling+Separation
SPB.33 M=PC(LS)=PS(LS)* Mixing+Separation
SPB.34 M=R(L)=PC(LS)=PS(LS)* Mixing+Reaction+Separation
Page 164
Case Studies
144
SPB.35 M=ES(H)=PC(LS)=PS(LS)* Mixing+Heating+Separation
SPB.36 M=ES(C)=PC(LS)=PS(LS)* Mixing+Cooling+Separation
SPB.37 M=ES(H)=R(L)=PC(LS)=PS(LS)* Mixing+Heating+Reaction+Separation
SPB.38 M=ES(C)=R(L)=PC(LS)=PS(LS)* Mixing+Cooling+Heating+Separation
SPB.39 M=PT(LS)=PS(LS) Mixing+Separation
SPB.40 M=ES(C)=PT(LS)=PS(LS) Mixing+Cooling+Separation
SPB.41 M=ES(H)=PT(LS)=PS(LS) Mixing+Heating+Separation
SPB.42 M=2phM=PC(VL)=PT(VL)=PS(VL)* Mixing+Separation
SPB.43 M=2phM=ES(H)= PC(VL)=PT(VL)=PS(VL)* Mixing+Heating+Separation
SPB.44 M=2phM=ES(C) =PC(VL)=PT(VL)=PS(VL)* Mixing+Cooling+Separation
SPB.45 M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)* Mixing+Reaction+Separation
SPB.46 M=2phM =R(V)=ES(H) =PC(VL)=PT(VL)=PS(VL)* Mixing+Reaction+Heating+Separation
SPB.47 M=2phM=R(V)=ES(C)=PC(VL)=PT(VL)=PS(VL)* Mixing+Reaction+Cooling+Separation
SPB.48 M=PC(LL)=PT(LL)=PS(LL)* Mixing+Separation
SPB.49 M=ES(H)= PC(LL)=PT(LL)=PS(LL)* Mixing+Heating+Separation
SPB.50 M=ES(C) =PC(LL)=PT(LL)=PS(LL)* Mixing+Cooling+Separation
SPB.51 D Stream division
• Step 8: Generation of phenomena based superstructure
The phenomena based superstructure is generated by using the algorithm A3.3. The
mathematical combinatorial superstructure (Figure 6.40) is combined with principle
PBBs from Table 6.25 to generate phenomena based superstructure. The possible outlet
phase is also identified and marked. In this case study, ethanol (D) and acetic acid (F) are
unwanted byproducts and are thus considered to be removed prior to removal of water.
This is also because of the fact that, succinic acid is highly soluble in water and thus other
impurities need to be removed prior to the removal of water in order to recover pure
crystalline succinic acid. It also makes necessary for the last task to contain ‘PT(LS)’
phenomena (indicated with the dash line). The phenomena based superstructure thus
generated is shown in Figure 6.41. The repetitive PBBs are marked in green color.
• Step 9: Reduction of alternatives and generation of basic structures
- S9.1. Reduction of alternatives
The reduction of alternatives is performed at 3 different levels under feasibility rules
and logical rules.
Feasibility rules
Firstly, the phenomena based superstructure is reduced by applying feasibility
rules at two different levels as mentioned in algorithm A3.4. Following the
algorithm, the outlet of the reactor is in solid-liquid phase with biomass which is
the first separation task and s taken into consideration. Non-condensable gases
are considered to be removed from the fermenter itself.
Page 165
6.3. Case study 3: Production of Bio-Succinic Acid
145
Figure 6.41: Generated phenomena based superstructure
F/EG
PT(MLL), PS(LL)PT(MVL), PS(VL)
F/GE
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
D/EG
PT(MLL), PS(LL)PT(MVL), PS(VL)
PT(LS), PS(LS), ES(C/H)
D/GE
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
--DE/G--E/G—EF/G--
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)2phM, PC(VL), PT(VL), PS(VL)*, ES(C), ES(H)
PC(LL), PT(LL), PS(LL)*PC(LS), PS(LS)*
E/G
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)2phM, PC(VL), PT(VL), PS(VL)*, ES(C), ES(H)
PC(LL), PT(LL), PS(LL)*PC(LS), PS(LS)*
D/EFG
PT(MLL), PS(LL)PT(MVL), PS(VL)
PT(LS), PS(LS), ES(C/H)
D/FGE
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
D/GEF
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
F/DEG
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
F/EGD
PT(MLL), PS(LL)PT(MVL), PS(VL)
F/GDE
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
L-LV-LL-S
V-LL-LV-LV-L
L-S
V-LL-LV-LV-L
L-S
L
Separation task - 2 Separation task - 3 Separation task - 4
2phM, R(L)
Fermentation
--DEFGIJ--
Reaction task
PC(LS), PS(LS)
DEFGI/J
Separation task - 1
DF/GE
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
FD/GE
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
DF/EG
PT(MLL), PS(LL)PT(MVL), PS(VL)
FD/EG
PT(MLL), PS(LL)PT(MVL), PS(VL)
PS(VL), ES(C), ES(C/H)
V-L
L-S
L-S L
V-L
L-S
L-LV-L
V-LL-LV-LV-L
L-S
V-LL-LV-LV-L
L-S
L-LV-L
L-LV-LL-S
L-LV-L
V-LL-LV-LV-L
L-S
L-LV-LL-S
V-LL-LV-LV-L
L-S
FDE/G
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)2phM, PC(VL), PT(VL), PS(VL)*, ES(C), ES(H)
PC(LL), PT(LL), PS(LL)*PC(LS), PS(LS)*
EFD/G
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
DEF/G
PT(VL), PS(VL)PT(MLL), PS(LL)PT(MVL), PS(VL)
2phM, PC(VL), PT(VL), PS(VL), ES(C), ES(H)
PT(LS), PS(LS), ES(C/H)
V-LL-LV-LV-L
L-SV-L
L-LL
V-LL-LV-LV-L
L-S
V-LL-LV-LV-L
L-S
Page 166
Case Studies
146
Further, looking at the phenomena based feasibility rules at level 2, infeasible
phenomena with boiling and meting point are removed.
Logical rules
At level 3 reduction (logical rules), the phase of inlet and outlet conditions are
checked and thus, PBBs that does not satisfy the logical rules in algorithm A3.4
are removed. The superstructure maintains its originality here at this level.
The updated superstructure after all reductions is shown in Figure 6.42.
- S9.2. Generation of basic structures The principle PBBs in phenomena-based superstructure (Figure 6.42) are translated
to basic structures using the algorithm A3.5. These basic structures in the form of
superstructure (level 1) is shown in Figure 6.43.
Further, the separation of E and G includes mass separating agent (MSA) that needs
additional separation task. Thus, the basic structures are also identified to recover the
MSA (Step A3.5.11). A desired MSA should be recovered easily and thus should not
form any azeotrope with the considered compounds in the system. The MSA should
take the compound present in lower amount i.e. succinic acid and must have lower
boiling point than succinic acid as water is a lower boiling component than product.
A potential solvent is identified later based on feasible threshold values for the
properties valid for the phenomena’s ‘PT(VL), ES(C), ES(H), PT(MLL), PT(MVL)’ or
literature search. Thus, the basic structures generated by following step A3.5.11 from
the feasible list of SPBs is shown alongside in Figure 6.43.
• Step 10: Combination of basic structure to generate flowsheet alternatives
The basic structures within the superstructure at level 1 are combined at two different
levels i.e. level 2 and 3 using algorithm A3.6. The biomass separation is only considered
for combination with fermentation step. Also, the tasks having a dashed line are not
combined as they signify that the last separation task needs ‘PT(LS)’ PBB. The
superstructures generated at level 2 and level 3 are shown in Appendix G.3.
• Step 11: Translation of the basic structure to unit-operation
The basic structures performing different tasks are translated to unit-operations using
algorithm A3.7. A selected list of alternatives generated is given in Appendix G.4. Figure
6.44 gives an overview of some of the basic structures translated to unit operation, some
of them are novel. The alternatives generated includes the base case which is the starting
point for this case study. The framework also generates the 3 intensified flowsheet
alternatives including membrane crystallizer and membrane bio-reactor shown in
section 6.3.2.
Page 167
6.3
. C
ase
stu
dy
3: P
rod
uct
ion
of
Bio
-Su
ccin
ic A
cid
14
7
Fig
ure
6.4
2:
Ph
en
om
en
a b
ase
d s
up
ers
tru
ctu
re a
fte
r a
pp
lyin
g r
ed
uct
ion
ru
les
F/E
G
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
D/E
G
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
PT
(LS
), P
S(L
S),
ES
(C/H
)
D/G
E
PT
(VL),
PS
(VL)
2phM
, P
C(V
L),
PT
(VL),
P
S(V
L),
ES
(C),
ES
(H)
--E
/G—
(or
FE
/G o
r D
E/G
)--
PT
(VL),
PS
(VL)
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
2phM
, P
C(V
L),
PT
(VL),
P
S(V
L),
ES
(C),
ES
(H)
PT
(LS
), P
S(L
S),
ES
(C/H
)2phM
, P
C(V
L),
PT
(VL),
P
S(V
L)*
, E
S(C
), E
S(H
)P
C(L
L),
PT
(LL),
PS
(LL)*
PC
(LS
), P
S(L
S)*
E/G
PT
(VL),
PS
(VL)
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
2phM
, P
C(V
L),
PT
(VL),
P
S(V
L),
ES
(C),
ES
(H)
PT
(LS
), P
S(L
S),
ES
(C/H
)2phM
, P
C(V
L),
PT
(VL),
P
S(V
L)*
, E
S(C
), E
S(H
)P
C(L
L),
PT
(LL),
PS
(LL)*
PC
(LS
), P
S(L
S)*
D/E
FG
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
PT
(LS
), P
S(L
S),
ES
(C/H
)
D/F
GE
2phM
, P
C(V
L),
PT
(VL),
P
S(V
L),
ES
(C),
ES
(H)
D/G
EF
PT
(VL),
PS
(VL)
F/E
GD
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
L-L
V-L
L-S
L-S
L
Sep
ara
tio
n t
as
k -
2S
ep
ara
tio
n t
as
k -
3S
ep
ara
tio
n t
as
k -
4
2phM
, R
(L)
Fe
rme
nta
tion
--D
EF
GIJ
--
Reac
tio
n t
ask
PC
(LS
), P
S(L
S)
DE
FG
I/J
Sep
ara
tio
n t
as
k -
1
DF
/GE
PT
(VL),
PS
(VL)
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
2phM
, P
C(V
L),
PT
(VL),
P
S(V
L),
ES
(C),
ES
(H)
PT
(LS
), P
S(L
S),
ES
(C/H
)
V-L
L-S
L
L-L
V-L
V-L
L-L
V-L
V-L
L-S
L-L
V-L
L-L
V-L
L-S V
-L
V-L
PT
(VL),
PS
(VL)
PT
(MLL),
PS
(LL)
PT
(MV
L),
PS
(VL)
2phM
, P
C(V
L),
PT
(VL),
P
S(V
L),
ES
(C),
ES
(H)
PT
(LS
), P
S(L
S),
ES
(C/H
)2phM
, P
C(V
L),
PT
(VL),
P
S(V
L)*
, E
S(C
), E
S(H
)P
C(L
L),
PT
(LL),
PS
(LL)*
PC
(LS
), P
S(L
S)*
DF
E/G
Page 168
Cas
e S
tud
ies
14
8
Fig
ure
6.4
3: L
ev
el
1 su
pe
rstr
uct
ure
wit
h t
ran
sla
ted
pri
nci
ple
PB
Bs
to b
asi
c st
ruct
ure
s
F/E
G
D/E
G
D/G
E
--E
/G—
(or
FE
/G o
r D
E/G
)--
E/G
D/E
FG
D/F
GE
L-S
L
Sep
ara
tio
n t
as
k -
2S
ep
ara
tio
n t
as
k -
3S
ep
ara
tio
n t
as
k -
4
Fe
rme
nta
tion
--D
EF
GIJ
--
Reac
tio
n t
ask
DE
FG
I/J
Sep
ara
tio
n t
as
k -
1
DF
/GE
L-S
LM
=2
phM
=R
(L)
M=
PC
(LS
)=P
S(L
S)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
M=
PT
(LS
)=P
S(L
S)
M=
ES
(C/H
)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
D/G
EF
M=
PC
(VL
)=P
S(V
L)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
M=
PT
(LS
)=P
S(L
S)
M=
ES
(C/H
)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
F/E
GD
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
S(V
L)
M=
PC
(VL
)=P
S(V
L)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
M=
PT
(LS
)=P
S(L
S)
M=
ES
(C/H
)
DF
E/G
M=
PC
(VL
)=P
S(V
L)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
M=
PC
(TS
)=P
S(L
S)
M=
ES
(C/H
)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)*
=P
S(V
L)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(LL
)=P
T(L
L)=
PS
(LL
)*
M=
PC
(LS
)=P
S(L
S)*
M=
PC
(VL
)=P
S(V
L)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
M=
PT
(LS
)=P
S(L
S)
M=
ES
(C/H
)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)*
=P
S(V
L)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(LL
)=P
T(L
L)=
PS
(LL
)*
M=
PC
(LS
)=P
S(L
S)*
M=
PC
(VL
)=P
S(V
L)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
M=
PT
(LS
)=P
S(L
S)
M=
ES
(C/H
)
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)*
=P
S(V
L)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(LL
)=P
T(L
L)=
PS
(LL
)*
M=
PC
(LS
)=P
S(L
S)*
M=
ES
(C)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
ES
(H)=
PC
(VL
)=P
T(V
L)=
PS
(VL
)
M=
PT
(ML
L)=
PS
(LL
)
M=
PT
(MV
L)=
PS
(VL
)
S*/
G
L-L
L-L
L-L
L-L
L-S
V-L
L-S
L-L
V-L
L-S
V-L
V-L V-L
V-L
L-L
V-L
V-L
V-L
V-L
V-L
V-L
V-L
LL-L
V-L
L-L
L-S
V-L
V-L
V-L
LL-L
V-L
V-L
V-L
L-L
Page 169
6.3. Case study 3: Production of Bio-Succinic Acid
149
Figure 6.44: Combination of basic structures-(A)-Membrane bio-reactor, (B)-Membrane crystallizer, (C)-Extractive divided wall column, (D)-L-L membrane extraction
M=PT(MLL)=PS(LL)
M=ES(C)
M=PT(LS)=PS(LS)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)*
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PT(MLL)=PS(LL)
M=2phM=R(L)
M=PC(LS)=PS(LS)
Basic strucutre Unit-operation
(A)
(B)
(C)
(D)
Non cond. gases
Glucose, Water
CO2Fermentation
broth
Succinic Acid
crystals
Waste
water
Succinic Acid
+ Water
Succinic Acid
+ Water
Succinic Acid +
Water
Water
MSA
MSA
Succinic Acid
+ Water
Water
MSA
Succinic
Acid + water
MSA
Page 170
Case Studies
150
Figure 6.45 gives an overview of generation of process alternatives at different steps while
applying the framework.
Figure 6.45: Generation and screening of alternatives at different steps
Stage IV: Ranking, analysis and comparison
• Step 12: Ranking and verification of generated flowsheet alternatives
- S12.1. Ranking of unit-operation based flowsheet alternatives Table 6.28 shows the 3 alternatives along with thier Enthalpy Index (EI) at different
levels. These are the selected alternatives that does not consider individual recovery
of unwanted by products.
Table 6.28: Enthalpy index for flowsheet alternatives at different levels
Level Alternative
No. Flowsheet alternative EI
3 773 Membrane bio-reactor → Carbon treatment → Adsorptive
membrane crystallizer (L-L membrane) 1.000
2 787 Membrane bio-reactor → L-L membrane extraction → Carbon
treatment → Crystallization 0.999
1 250 Fermenter → Microfiltration→ Carbon treatment → Liquid-
liquid membrane → Crystallization→ 0.997
- S12.2. Verification of selected flowsheet alternative
In this section of the case study, the selected alternative is verified and analyzed in
order to compare with the base case and previously generated intensified alternatives.
The three alternatives presented in section 6.3.2 are also generated in this framework.
In this alternative, the membrane bio-reactor performs the fermentation at desired
conditions and allows the biomass free fermentation broth to pass through the
1080
26332
874
789
Mathematical
alternatives
All possible
combination of SPB’s
Total number of
alternatives before
combination
(feasible + infeasible)
Total number of alternatives
(feasible including novel
and intensified solutions)
Page 171
6.3. Case study 3: Production of Bio-Succinic Acid
151
membrane. Same hypothesis as in flowsheet alternative 1 of section 6.3.1 is also
considered here. The clarified broth is then passed through liquid-liquid extraction
column with an inbuilt membrane module. The novel equipment separates most of
the water from the clarified broth and the mass separating agent (ionic liquid) is
recovered to be sent back for the makeup. The leftover is then passed through
activated carbon to remove colored impurities. Then the outlet is fed to crystallizer
to obtain pure succinic acid crystals. A hydrophobic phosphonium based ionic liquid
has been used for multistep extraction of the bio-succinic acid (Oliveira, 2012). The
membrane data for separation of hydrophobic ionic liquid from mixture of water and
organic acid is taken from Zhang et al. (2017). The membrane separates the mixture
at high efficiency of >98% and high flux rate to keep the membrane area in acceptable
range based on the super wettability phenomena. The schematic of this alternative is
shown in Figure 6.46. The alternative is simulated in PRO/IITM to resolve the mass
and energy balance to be used for further analysis.
Figure 6.46: Schematic of process alternative 4 (787)
• Step 13: Analysis and comparison of selected flowsheet alternatives
- S13.1. Analysis of selected alternatives
The selected flowsheet alternative from step 12 is analyzed in terms of economics,
sustainability parameters and LCA to generate the values of performance indicators.
The parameters calculated are shown in Table 6.29. The analysis does not include the
cost of ionic liquid.
- S13.2. Comparison of selected alternatives
In this step, the comparison (Table 6.29) of above alternative is made with the base
case and alternatives from section 6.3.2. Various parameters at general level for
example, purity, target production, RM cost etc. are selected including sustainability
and LCA indicators like HTPI (human toxicity potential by ingestion), PCOP (photo
chemical oxidation potential) and GWP is global warming potential.
Succinic Acid
crystals
Waste waterFermentation
broth
Waste
water
Act. CarbonSuccinic Acid + water
MSA
Non cond. gases
Glucose, Water
CO2
Recovered MSA
Spent
Carbon
Membrane bio-reactor
Membrane liquid-liquid
extractor
Adsorption column
Crystallization
Page 172
Case Studies
152
Table 6.29: Analysis of results for base case and generated intensified alternatives
Parameter Base Case
Alternative 1
(429)
Alternative 2
(668)
Alternative 3
(724)
Alternative 4
(787)
General results Succinic Acid Production (kt/y) 30.00 30.31 32.32 32.65 32.48
Succinic acid purity (wt. %) >99 >99 >99 >99 >99
Utility Cost (M$/y) 4.95 4.13 4.98 4.16 1.26
Raw material cost (M$/y) 29.04 29,09 29.04 29.09 28.94
RM (Glucose) loss (kt/y) 1.49 1.49 1.49 1.49 1.49
Total Process water (kt/y) 13,534.07 11,447.73 13,534.07 11,447.73 11,447.73
Number of unit operations 6 5 5 4 5
Performance
metrics
Succinic acid (kg/kg main RM) 0.86 0.87 0.92 0.93 0.93
Utility cost ($/kg product) 0.16 0.14 0.15 0.13 0.10
RM Cost ($/kg product) 0.97 0.96 0.90 0.89 0.89
Product sale ($/y) 8,58,09,289 8,66,76,411 9,24,46,064 9,33,80,221 9,29,00,753
LCA results GWP (CO2 eq.) 5.41 4.48 5.02 4.16 0.19
HTPI (1/LD50) 2.66E-04 2.20E-04 2.47E-04 2.04E-04 3.21E-05
PCOP 1.50E-01 1.24E-01 1.39E-01 1.15E-01 6.14E-05
HTC (kg benzene eq.) 3.74E+00 3.10E+00 3.48E+00 2.87E+00 7.45E-05
The 4 alternatives are more sustainable and economic than the base case for example resulting
in nearly 22 % reduction in utility cost and 23 % reduction in the global warming potential for
alternative 3 (724), employing membrane bio-reactor and membrane crystallizer. The alternative
787 has approximately 74 % less utility cost and extremely low sustainability and LCA indicators,
owing to highly selective and permeable membrane for separating ionic liquid. Alternative 787
presents the best results among all selected alternatives as compared to the base case. For each
of the alternatives the product purity has been kept or improved from the base case while
maintaining the production target. The number of unit operations have been reduced in all the
alternatives in comparison to the base case (Table 6.29).
A graphical comparison of all the generated alternatives with the base case is shown in Figure
6.47 as a radar plot. The radar plot confirms that the generated alternatives are more sustainable
and non-trade-off, in terms of the selected performance criteria. Here, the outer boundary of the
plot represents the base case design while all the more sustainable alternatives should be within
the boundary. The values are calculated by taking percentage ratios of different factors with
respect to the base case except product (kg/kg RM) where inverse ratio has been taken. Also, in
Figure 6.47 due to considerably low values of HTPI and GWP for alternative 787, a factor of 5
Page 173
6.3. Case study 3: Production of Bio-Succinic Acid
153
and 15 is taken for comparison. Here, RM is raw material, HTPI is human toxicity potential by
ingestion, GWP is global warming potential and HTC is Human Toxicity Carcinogenic.
Figure 6.47: Comparison of economic and LCA improvements relative to the base case
Further, recalling the design targets set in step 4, which are required to be met in order to achieve
more sustainable, economic and innovative solutions. These are as follows:
- Reduce energy consumption –Yes (<40 % reduction annually)
- Reduce utility cost - Yes (12-37 % reduction per kg of product)
- Improvement in LCA/sustainability indictors – Yes (>7 % reduction)
- Unit operation reduction – Yes (1-2)
- Product purity (to be kept at least as base case) – Yes (achieved as required)
- Production target (to be kept at least as base case) – Yes (achieved as required)
- Waste minimization – Yes (<15 % reduction annually)
- Increase product recovery – Yes (<8 % increase annually)
6.3.4. Discussion
A brief summary for the production of bio-succinic acid case study utilizing CO2 is shown in
Figure 6.48. The results are shown across 3 sections (6.3.1-6.3.3) and how the process alternatives
are identified using different approaches. More than 11,500 alternatives are generated while
synthesizing the optimal processing route using the superstructure network optimization based
50%
60%
70%
80%
90%
100%
Product (kg/Kg main RM)^-1
Utility cost (USD/kg product)
RM Cost (USD/kg product)
RM (Glucose) loss (kT/yr)GWP (CO2 eq.)
HTPI(1/LD50)
Process water (kg/kg of product)
Base Case Alternative 1 Alternative 2 Alternative 3 Alternative 4
Page 174
Case Studies
154
approach out of which more than 2,600 alternatives are found feasible along with existing routes.
The optimal processing route is identified as a novel process alternative to produce bio-succinic
acid. The selected alternative is then designed and analyzed in detail to identify process hotspots
and set targets for improvement. Further, the framework developed in this work is applied on
the same base case identified using superstructure optimization. The framework generates over
700 alternatives including the solutions generated using extended phenomena-based synthesis
method. Some of the alternatives are feasible but may not be practically applicable as they require
either high membrane area or high amount of adsorbent to remove large volume of water. The
novel and intensified flowsheet alternatives are verified and analyzed further and compared with
the base case to achieve set design targets.
Figure 6.48: Summary of results for production of bio-succinic acid
This case study presents the capability of the framework to generate wide range of novel and
innovative solutions involving a bioprocess. The intensified alternative with the membrane
crystallizer may also be studied by performing experiments for verification. While, membrane
bio-reactors involving in-situ product removal are well known techniques. The methodology also
generates another potential novel intensified equipment involving extraction and membrane
separation in a single unit significantly improving results.
6.4. Chapter summary
The chapter presents 3 case studies spanning chemical and biochemical process applications.
The chapter also shows key feature of the framework to perform direct and indirect phenomena
based synthesis-intensification. Out of the 3 case studies, first case study is an example of direct
Flowsheet alternatives
Total alternatives: 11520
Feasible alternatives: 2604
Existing routes generated: 5
Flowsheet alternatives
Intensified alternatives: 3
Flowsheet alternatives
Total feasible alterantives: 789
Selected alternatives: 4
Superstructure Optimization
Detailed design and analysisPhenomena based intensification
Integrated phenomena-based
synthesis-intensification
3 different scenarios
Synthesis and Design Extended Phenomena-based
synthesis-intensificationPBS-Intensification
Novel processing route
Indirect approach
Novel Unit-operations
Novel Unit-operations
Page 175
6.4. Chapter summary
155
synthesis while other two are performed via indirect synthesis-intensification. Further, for
indirect synthesis-intensification, in case study 2, a base case flowsheet is used from literature.
While in case study 3, the base case is first synthesized using mathematical optimization of the
superstructure of alternatives. An overview of the case studies is shown in Table 6.30.
Table 6.30: Overview of 3 case studies solved using PBS-Intensification method
Case study 1
(DME)
Case study 2
(Toluene)
Case study 3
(Bio-succinic acid)
Problem type Direct Indirect Indirect
Base Case flowsheet used No Yes Yes
Base case source - Tula, 2016 Synthesized
No. of mathematical alternatives 6 39636 1080
No. of feasible flowsheets 88 726 789
No. of alternatives analyzed 3 3 5
Performance criteria Achieved Achieved Achieved
For all the case studies, several innovative solutions with number of potentially feasible novel
unit-operations are synthesized. The selected novel intensified unit-operations are validated by
using simple mass and energy balance models to show feasibility. These unit-operations can be
further validated by performing detailed modelling and experiments.
Page 176
Case Studies
156
Page 177
6.4. Chapter summary
157
PART - IV
This is the last part of the thesis, where necessary conclusions are
drawn from the research presented in this work. The main
highlights of the framework from perspective of achievements
are presented. The conclusions are then drawn on the basis of the
novelty of the work and research challenges addressed from the
viewpoint of process intensification (PI) in process systems
engineering (PSE). Further, results of the case studies are briefly
discussed in lieu of the framework developed (chapter 7). Finally,
some of the open challenges that could be addressed in future
research to make the framework more robust and develop a
possible interactive tool out of it are discussed (chapter 8).
Page 178
Case Studies
158
Page 179
159
Chapter 7 Conclusions
In this chapter of the thesis, the achievements and conclusions are presented. The
achievement section presents the main highlights of the developed framework.
Then, conclusion section provides a summary of the need for innovative solutions,
the developed framework, its key features and the application case studies.
Chapter outline:
7.1. Achievements
7.2. Conclusions
Page 180
Conclusions
160
7.1. Achievements
In this work, the main achievement is the development of a systematic framework to perform
process synthesis-intensification generating novel, innovative and intensified process flowsheet
alternatives. The main highlights of the bottom-up approach (phenomena) based framework are
as follows:
• The framework can be applied for both direct (new) and indirect (existing) synthesis-
intensification problems.
• The framework based on the decomposition strategy starting at the lowest level of
aggregation (phenomena) does not need detailed or rigorous models at every decision
making step of synthesis-intensification.
• The framework enables a systematic generation of the completely new and novel unit-
operation based flowsheet alternatives without any pre postulation.
• The framework covers a complete search space of possible phases including vapor, liquid
and solid systems at phenomena scale.
• The framework has the potential to generate novel solutions based on special energy
sources operating at lower level of aggregation.
• The framework generates a phenomena based superstructure consisting of all possible
solutions covering complete feasible search space for considered problem.
• The framework allows to rank and select novel and intensified alternatives based on
Enthalpy Index (EI) for detailed analysis and comparison.
• The framework is flexible to handle changes, extensions or different types of chemical
and biochemical processes.
• The framework incorporates economic, life cycle and sustainability analysis to assist in
generation of potential green solutions.
• The framework can be easily translated to an interactive systems engineering tool as it is
based on database, knowledge base and systematic algorithms and rules for every step.
The successful application of the framework for three different case studies shows the capability
of the framework to systematically generate potential novel, innovative and intensified flowsheet
alternatives. The framework presented in this work fulfills the challenges a) and d) mentioned in
the section 2.1 (chapter 2) completely as it is capable of generating non trade off, sustainable and
innovative solutions systematically while partially b) and d) as the future work (chapter 8)
incorporates addition of operability and safety parameters to screen and assess the different
solutions while managing the complexity inherited by them.
Page 181
161
7.2. Conclusions
The traditional concepts of process synthesis need to be expanded in order to generate novel and
innovative solutions that can significantly improve process performance to cope up with global
competition, economics and induce sustainability. Process intensification (PI) has proven its
potential to generate solutions that bring significant improvements in terms of size, economics,
efficiency, and sustainability. Though, full potential of PI is yet to be unfolded. One of the
highlighted PI approach that guarantees to generate novel and innovative solutions is bottom-
up approach. This solves the challenge of process synthesis by departing from conventional
approach and thus operating at lower level of aggregation. Within bottom-up approaches, several
methodologies have been developed solving different types of problems including simultaneous
synthesis and intensification within a single framework. This allows to incorporate process
intensification principles during process synthesis. However, these simultaneous approaches are
not integrated enough to directly synthesize intensified solutions without a priori information.
In this work, a systematic phenomena-based synthesis-intensification framework is developed.
The framework consists of 4 stages and 13 steps. Several algorithms and knowledge base are also
developed to aid systematic solution generation. The developed framework is different from
other bottom-up approaches as it is not iterative and does not completely depend upon
mathematical optimization based techniques. Here, the synthesis-intensification problem is
solved by decomposition into different parts and then simultaneously generating both novel and
intensified solutions starting from phenomena. Unlike enumeration techniques that struggle
with exponentially increasing combinations, in this framework it is tackled by introducing
ranking based on enthalpy index (EI). The explosion of alternatives generated using the
mathematical combinatorial algorithms are countered using logical and feasibility reduction
rules. These rules are based on the thermodynamic insights, thus making them feasible to be
considered for further analysis. The framework also includes economic, sustainability and life
cycle analysis to compare and ensure that selected alternatives are sustainable solutions.
One of the key novelties of this framework is that it not only generates more economic and
sustainable novel intensified solutions for an existing process but also can perform simultaneous
direct synthesis-intensification via generation of phenomena based superstructure to achieve
desired objectives without any prior postulation of equipments or any process information. The
solutions are generated at different levels using combinatorial rules i.e. flowsheet options based
on existing equipments, existing intensified equipments and completely novel equipment. The
framework does not claim to generate global optimal solutions.
The framework was applied to three different case studies performing direct and indirect
synthesis-intensification. The case studies span chemical and biochemical process applications.
DME case study shows that novel and intensified solutions can be generated at different levels
Page 182
Conclusions
162
by application of the framework without any prior information and pre postulation about the
equipment. The framework generates novel flowsheet alternatives including both existing and
novel equipments (reactive distillation vapor permeation in a single unit (RDVPSU)). The novel
equipment performs all the required tasks to obtain pure DME while saving around 29 % energy
with significant reduction in environmental parameters as compared to conventional process.
The HDA of toluene and biological production of succinic acid case study are application of
indirect synthesis-intensification. In HDA of toluene, an existing process flowsheet is taken from
literature as the base case while in bio-succinic acid case study the base case is synthesized using
mathematical optimization of superstructure approach. In both the case studies more
sustainable, economic and novel process flowsheet alternatives are synthesized as compared to
the base case. The novel flowsheet alternative in HDA case study reduces the annual hydrogen
loss by 96 % and energy consumption by 10-15 % as compared to the base case. In bio-succinic
acid case study, all the alternatives from synthesis to intensification are novel with novel
equipments like membrane crystallizer and membrane based liquid-liquid extraction. Here, the
intensified solutions result in 12-37 % reduction of utility cost while increasing the product
recovery up to 8 percent.
It should be noted that the novel and intensified unit-operations generated in this work are
simulated using simple models (with experimental data from literature). The novel solutions
generated that are verified using simple models can be further verified by performing detailed
modelling and experimentation.
Page 183
163
Chapter 8 Future Perspectives
In the last chapter of the thesis, some of the open challenges that could be used for
future research are presented. The challenges for example introduction of safety
and operability, expansion of knowledge bases, more layer of ranking could make
the methodology more robust are mentioned.
Chapter outline:
8.1. Open challenges and future work
Page 184
Future Perspectives
164
8.1. Open challenges and future work
The challenges that can be addressed in the future research are as follows:
• Inclusion of the operability and safety analysis: Generation of intensified unit-
operations (single unit-operation performing multiple tasks) sometimes significantly
reduces the degree of freedom. Thus, easy operability and considerate safety may become
an issue while realizing these solutions at practical level. So, operability is a key issue to
be addressed while generating intensified alternatives. Thus, the current framework can
be extended by incorporating operability and safety analysis in stage IV of the framework.
This can also be added as a part of the ranking where alternatives ranked better on the
operability and safety at different levels are considered for detailed analysis.
• Additional layers for ranking of alternatives: Currently, the alternatives are ranked
based on Enthalpy Index (EI), which is the lone parameter for ranking in this framework.
This is justified as ready information is not available for new equipments. Also, the
generation of equipments is not known apriori which restricts the development of simple
models. Though, EI alone, is not sufficient to preselect alternatives from simplification,
possible assumptions and solution feasibility point of view. Thus, additional layers of the
ranking are also required to rank the flowsheet alternatives. Some of the options for
future work are to include simplified Gibbs free energy and entropy calculations.
• Framework to a tool: As the framework is systematic and is based on algorithms and
rules developed at each step, it has potential to develop as a tool where certain parts of
the framework requires human interaction. This kind of tool can quickly generate
alternatives where it can be integrated with ICAS (Gani et al. 1997; Gani 2002) property
database to fetch information about the components while missing properties can be
automatically generated using algorithm behind ProPred tool of ICAS. Also, the current
implementation of framework is very convenient and intuitive because of the developed
knowledge bases. However, generating novel and intensified solutions may significantly
benefit by incorporating the algorithms to a dedicated modeling and optimization
environment such as GAMS (GAMS Development Corporation, 2012).
• Expansion of reduction algorithms: The reduction algorithms helps in reducing
infeasible and not logical alternatives from the superstructure. More constraints can be
added here depending on the problem type to reduce the number of alternatives to be
ranked and analyzed in stage IV of the framework.
• Expansion of phenomena database and knowledge bases: The strength of the
framework lies in the generation of alternatives using its phenomena database and
knowledge bases where several algorithms are developed. These can be developed and
extended further to bring new dimension from transport phenomena point of view.
Page 185
References
165
References References
Agreda V. H., Partin L. R. & Heise W. H., 1990. “High-purity methyl acetate via reactive
distillation”. Chemical Engineering Prog, 86(2), 40–46.
Anxionnaz, Z., Cabassud, M., Gourdon, C. & Tochon, P., 2008. “Heat exchanger/reactors (HEX
reactors): concepts, technologies: state-of-the-art”, Chemical Engineering Processing: Process
Intensification, 47(12), 2029-2050.
Arizmendi-Sánchez, J.A. and Sharratt, P.N., 2008. “Phenomena-based modularisation of
chemical process models to approach intensive options”, Chemical Engineering Journal, 135(1-
2), 83-94.
AspenPlus, http://www.aspentech.com (accessed 13 August, 2019).
Asprion, N. and Kaibel, G., 2010. Dividing wall columns: fundamentals and recent advances.
Chemical Engineering and Processing: Process Intensification, 49(2), 139-146.
Azizi, Z., Rezaeimanesh, M., Tohidian, T. and Rahimpour, M.R., 2014. “Dimethyl ether: A review
of technologies and production challenges”, Chemical Engineering and Processing: Process
Intensification, 82, 150-172.
Babi, D. K., Holtbruegge, J., Lutze, P., Górak, A., Woodley, J. M. & Gani, R., 2015. “Sustainable
process synthesis–intensification”, Computers & Chemical Engineering, 81, 218-244.
Babi, D.K., 2014. “Sustainable Process Synthesis-Intensification”. Technical University of
Denmark. Retrieved from https://orbit.dtu.dk/en/publications/sustainable-process-synthesis
intensification(56471a95-108c-444a-9a31-a6da209e0fdb).html
Babi, D.K., 2015. “Teaching Sustainable Process Design Using 12 Systematic Computer-Aided
Tasks”. Computer Aided Chemical Engineering, 37, 173-178.
Barton, P.I. and Pantelides, C.C., 1993. “gPROMS-A combined discrete/continuous modelling
environment for chemical processing systems”, Simulation Series, 25.
Bechthold, I., Bretz, K., Kabasci, S., Kopitzky, R. and Springer, A., 2008. “Succinic acid: a new
platform chemical for biobased polymers from renewable resources”, Chemical engineering &
technology, 31(5), 647-654.
Bîldea, C.S., Győrgy, R., Brunchi, C.C. and Kiss, A.A., 2017. “Optimal design of intensified
processes for DME synthesis”, Computers & chemical engineering, 105, 142-151.
Page 186
References
166
Bedenik, N.I., Pahor, B. and Kravanja, Z., 2004. “An integrated strategy for the hierarchical
multilevel MINLP synthesis of overall process flowsheets using the combined
synthesis/analysis approach”, Computers & chemical engineering, 28(5), 693-706.
Bernier, R.L., Dunuwila, D., Cockrem, M.C., Fruchey, O.S., Keen, B.T., Albin, B.A., Dombek, B.D.
and Clinton, N.A., Bioamber Sas, 2013. “Processes for purification of succinic acid via
distillation”, WO2013/088239A2.
Bertran, M.O., Frauzem, R., Sanchez-Arcilla, A.S., Zhang, L., Woodley, J.M. and Gani, R., 2017.
“A generic methodology for processing route synthesis and design based on superstructure
optimization”, Computers & Chemical Engineering, 106, 892-910.
Bessling, B., Schembecker, G., & Simmrock, K. H., 1997. “Design of processes with reactive
distillation line diagrams”, Ind Eng Chem Res, 36(8), 3032–3042.
Bouton, G.R. and Luyben, W.L., 2008. “Optimum economic design and control of a gas
permeation membrane coupled with the hydrodealkylation (HDA) process”, Industrial &
Engineering Chemistry Research, 47(4), 1221-1237.
Caballero, J. A. & Grossmann, I. E., 2004. “Design of distillation sequences: from conventional to
fully thermally coupled distillation systems”, Computers & Chemical Engineering 28(11), 2307–
2329.
Calabro, V., Jiao, B. L., & Drioli, E., 1994. “Theoretical and experimental study on membrane `
distillation in the concentration of orange juice”, Industrial & Engineering Chemistry Research
33 (7), 1803–1808.
Carvalho, A., Matos, H.A. and Gani, R., 2013. “SustainPro—A tool for systematic process analysis,
generation and evaluation of sustainable design alternatives,” Computers and Chemical
Engineering, 50, 8-27.
Cavani, F., Albonetti, S., Basile, F. and Gandini, A., 2016. “Chemicals and fuels from bio-based
building blocks”, John Wiley & Sons.
Chen, Q. and Grossmann, I.E., 2017. “Recent developments and challenges in optimization-based
process synthesis”, Annual review of chemical and biomolecular engineering, 8, 249-283.
Choi, S., Song, C.W., Shin, J.H. and Lee, S.Y., 2015. “Biorefineries for the production of top
building block chemicals and their derivatives”, Metabolic engineering, 28, 223-239.
Cignitti, S., 2014. “Computer-aided reaction path synthesis”, MSc thesis. Technical University of
Denmark (DTU), Kgs. Lyngby, Denmark.
Page 187
References
167
Costs of doing business in Thailand, 2014. http://www.thaiembassy.org/dakar/contents/files/
business-20150617-184429-264724.pdf (accessed March, 2017).
Chemcad, V., 2002. “Process Flow Sheet Simulator”, Chemstations Inc., Houston, 370, 371.
da Cruz, F.E. and Manousiouthakis, V.I., 2017. “Process intensification of reactive separator
networks through the IDEAS conceptual framework”, Computers & Chemical Engineering,
105, 39-55.
Datta, R., Glassner, D.A., Jain, M.K. and Roy, J.R.V., Michigan Biotechnology Institute, A
Michigan Corp and Michigan Biotechnology Institute East Lansing Michigan A Michigan
Corp, 1992. “Fermentation and purification process for succinic acid”, U.S. Patent 5,168,055A.
Demirel, S. E., Li, J. & Hasan, M. F., 2017. “Systematic process intensification using building
blocks”, Computers & Chemical Engineering 105, 2-38.
DOE, U., 2015. “Quadrennial technology review 2015”, US Department of Energy, Washington,
DC.
Donnelly, M.I., Millard, C.S., Chen, M.J., Rathke, J.W. and Clark, D.P., 1998. “A novel
fermentation pathway in an Escherichia coli mutant producing succinic acid, acetic acid, and
ethanol”, Biotechnology for Fuels and Chemicals, 187-198, Humana Press, Totowa, NJ.
Douglas, J.M., 1985. “A hierarchical decision procedure for process synthesis”, AIChE Journal,
31(3), 353–362.
Douglas, J.M., 1988. “Conceptual design of chemical processes”, Vol. 1110, New York: McGraw-
Hill.
Fischer, C.D. and Iribarren, O.A., 2011. “Mass integration as a design heuristic: improvements in
the HDA process”, Industrial & Engineering Chemistry Research, 50(22), 12664-12677.
Floudas, C.A., 1987. “Separation synthesis of multicomponent feed streams into multicomponent
product streams”, AIChE Journal, 33(4), 540–550.
Floudas, C.A., Ciric, A.R. & Grossmann, I.E., 1986. “Automatic synthesis of optimum heat
exchanger network configurations”, AIChE Journal, 32(2), 276–290.
Fontalvo, J.; Keurentjes, J. T. F. 2015. ”A Hybrid Distillation− pervaporation System in a Single
Unit for Breaking Distillation Boundaries in Multicomponent Mixtures”, Chem. Eng. Res. Des.,
99, 158−164.
Fox, J. A., Hildebrandt, D., Glasser, D. & Patel, B., 2013. “A graphical approach to process synthesis
and its application to steam reforming”, AIChE Journal, 59(10), 3714-3729.
Page 188
References
168
Freund, H. and Sundmacher, K., 2008. “Towards a methodology for the systematic analysis and
design of efficient chemical processes: Part 1. From unit operations to elementary process
functions”, Chemical Engineering and Processing: Process Intensification, 47(12), 2051-2060.
Gallucci, F., Tosti, S. & Basile, A., 2008. “Pd–Ag tubular membrane reactors for methane dry
reforming: a reactive method for CO2 consumption and H2 production”, Journal of Membrane
Science, 317(1), 96-105.
GAMS Development Corporation, 2012. “General Algebraic Modeling System (GAMS) Release
23.9.5”.
Gani, R., and Babi, D. K., 2014. ”Systematic Computer Aided Framework for Process Synthesis,
Design and Intensification”, T. Letcher, J. Scott, & P. A. Darrell (Eds.), Chemical Processes for
a Sustainable Future, 698–752. Cambridge: Royal Chemical Society.
Gani, R., 2002. “ICAS documentation”, CAPEC, Technical University of Denmark.
Gani, R., Hytoft, G., Jaksland, C., & Jensen, A. K. (1997). ”An integrated computer aided system
for integrated design of chemical processes”, Computers & Chemical Engineering, 21(10), 1135–
1146.
Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “Sustainable and Innovative
Solutions through an Integrated Systematic Framework”, Computer Aided Chemical
Engineering, 44, 1165-1170.
Garg, N., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “A Multi-stage and Multi-level
Computer Aided Framework for Sustainable Process Intensification,” Computer Aided
Chemical Engineering, 43, 875-880.
Garg, N., Tula, A.K., Eden, M.R., Kontogeorgis, G.M., Woodley, J.M. and Gani, R., 2018, “Hybrid
Schemes for Intensified Chemical and Biochemical Process Alternatives”, Chemical
Engineering Transactions, 69, 517-522.
Garg, N., Woodley, J.M., Gani, R. and Kontogeorgis, G.M., 2019. “Sustainable solutions by
integrating process synthesis-intensification”, Computers & Chemical Engineering, 126,
pp.499-519.
Gerberding, S.J. and Singh, R., Gerberding Steven J, 2012. “Purification of succinic acid from the
fermentation broth containing ammonium succinate”, U.S. Patent 0,289,742.
Glassner, D.A. and Datta, R., Michigan Biotechnology Institute A Corp Of Mi, 1992. “Process for
the production and purification of succinic acid”, U.S. Patent 5,143,834A.
Page 189
References
169
Graaf, V.D.M.J., Valianpoer, F., Fiey, G., Delattre, L. and Schulten, E.A.M., 2011. “Process for the
crystallization of succinic acid”, WO2011/064151A1.
Guettler, M.V., Jain, M.K. and Rumler, D., Michigan Biotechnology Institute, 1996. “Method for
making succinic acid, bacterial variants for use in the process, and methods for obtaining
variants”, U.S. Patent 5,573,931.
Guettler, M.V., Jain, M.K. and Soni, B.K., Michigan Biotechnology Institute, 1998. ”Process for
making succinic acid, microorganisms for use in the process and methods of obtaining the
microorganisms”, U.S. Patent 5,723,322.
Guettler, M.V., Rumler, D. and Jain, M.K., 1999. “Actinobacillus succinogenes sp. nov., a novel
succinic-acid-producing strain from the bovine rumen”, International Journal of Systematic
and Evolutionary Microbiology, 49(1), pp.207-216.
Haelssig, J. B.; Tremblay, A. Y.; Thibault, J., 2012. “A New Hybrid Membrane Separation Process
for Enhanced Ethanol Recovery: Process Description and Numerical Studies”, Chem. Eng. Sci.,
68, 492−505.
Halvorsen, I.J. and Skogestad, S., 2011. “Energy efficient distillation”, Journal of Natural Gas
Science and Engineering, 3(4), 571-580.
Harper, P. M., & Gani, R. (2000). “A multi-step and multi-level approach for computer aided
molecular design”, Computers & Chemical Engineering, 24(2-7), 677–683.
Harrison, R.G., Todd, P., Todd, P.W., Rudge, S.R., Petrides, D.P., 2015. “Bioseparations Science
and Engineering”, Oxford University Press.
Holtbruegge, J., Kuhlmann, H. and Lutze, P., 2015. “Process analysis and economic optimization
of intensified process alternatives for simultaneous industrial scale production of dimethyl
carbonate and propylene glycol”, Chemical Engineering Research and Design, 93, 411-431.
Hong, W.H., Lee, S.Y., Hong, Y.K., Won, H.J., Huh, Y.S., Song, H., Lee, E.Z., 2009. “Method for
purifying succinic acid by crystallization of culture broth”, WO2009/082050A1.
Hostrup, M., Gani, R., Kravanja, Z., Sorsak, A. and Grossmann, I., 2001. “Integration of
thermodynamic insights and MINLP optimization for the synthesis, design and analysis of
process flowsheets”, Computers & Chemical Engineering, 25(1), 73-83.
https://egypt-business.com/ticker/details/1814-dimethyl-ether-dme-market-by-type-andappli
cation ---global-industry-analysis-and-forecast-to-2023/253210 (accessed on March, 2019).
https://www.crystalmarketresearch.com/report-sample/CM11377 (accessed on March, 2019).
Page 190
References
170
https://www.technavio.com/report/global-succinic-acid-market, Global succinic acid market
2017-2021 (accessed on 12th Oct, 2018).
ICIS chemicals indicative pricing, https://www.icis.com/explore/chemicals/channelinfochemic
als-a-z/, accessesed in 2017
Industrial Price Comparison - Rocky Mountain Power, https://www.rockymountainpower.net
/about/rar/ipc.html, accessed in 2018.
Inoue, T., Nagase, T., Hasegawa, Y., Kiyozumi, Y., Sato, K., Nishioka, M., … Mizukami, F., 2007.
“Stoichiometric Ester Condensation Reaction Processes by Pervaporative Water Removal via
Acid-Tolerant Zeolite Membranes”, Industrial & Engineering Chemistry Research, 46(11),
3743–3750.
Intratec utility pricing, https://www.intratec.us/chemical-markets/cooling-water-cost#subtable,
(accessed in 2017).
Isar, J., Agarwal, L., Saran, S., Kaushik, R. and Saxena, R.K., 2007. “A statistical approach to study
the interactive effects of process parameters on succinic acid production from Bacteroides
fragilis”, Anaerobe, 13(2), 50-56.
Jaksland, C. & Gani, R., 1996. “An integreated approach to process/product design and synthesis
based on properties-process relationship”, Computers & Chemical Engineering, 20(96), S151–
S156.
Jaksland, C.A., Gani, R. & Lien, K.M., 1995. “Separation process design and synthesis based on
thermodynamic insights”, Chemical Engineering Science, 50(3), 511–530.
Jantama, K., Haupt, M.J., Svoronos, S.A., Zhang, X., Moore, J.C., Shanmugam, K.T. and Ingram,
L.O., 2008. “Combining metabolic engineering and metabolic evolution to develop
nonrecombinant strains of Escherichia coli C that produce succinate and malate”,
Biotechnology and bioengineering, 99(5), 1140-1153.
Kalakul, S., Malakul, P., Siemanond, K. and Gani, R., 2014. “Integration of life cycle assessment
software with tools for economic and sustainability analyses and process simulation for
sustainable process design”, Journal of cleaner production, 71, 98-109.
Kim, Y. H., Park, L. K., Yiacoumi, S. & Tsouris, C., 2017. “Modular Chemical Process
Intensification: A Review”, Annual Review of Chemical and Biomolecular Engineering, (0).
King, C.J. and Poole, L.J., 1995. “Carboxylic acid sorption regeneration process”, U.S. Patent
5,412,126.
Page 191
References
171
Kiss, A. and Suszwalak, D.P., 2012. “Enhanced dimethyl ether synthesis by reactive distillation in
a dividing-wall column”, Procedia Engineering, 42, 581-587.
Kiss, A.A., Pragt, H. and van Strien, C., 2007. “Overcoming equilibrium limitations in reactive
dividing-wall columns” Computer Aided Chemical Engineering, 24, 467-472.
Kokossis, A.C. and Floudas, C.A., 1994. “Stability in optimal design: synthesis of complex reactor
networks”, AIChE Journal, 40(5), pp.849-861.
Kokossis, A.C., 1990. “Optimization of complex reactor networks—I. Isothermal operation”,
Chemical Engineering Science, 45(3), pp.595-614.
Kuhlmann, H. and Skiborowski, M., 2017. “Optimization-based approach to process synthesis for
process intensification: General approach and application to ethanol dehydration”, Industrial
& Engineering Chemistry Research, 56(45), 13461-13481.
Kuhlmann, H., Veith, H., Moller, M., Nguyen, K.P., Górak, A. and Skiborowski, M., 2017.
“Optimization-Based Approach to Process Synthesis for Process Intensification: Synthesis of
Reaction-Separation Processes.”, Industrial & Engineering Chemistry Research, 57, 3639-3655.
Kuhn, J., Lakerveld, R., Kramer, H.J., Grievink, J. and Jansens, P.J., 2009. “Characterization and
dynamic optimization of membrane-assisted crystallization of adipic acid’, Industrial &
Engineering Chemistry Research, 48(11), 5360-5369.
Lee, P., Lee, S., Hong, S. and Chang, H., 2002. “Isolation and characterization of a new succinic
acid-producing bacterium, Mannheimia succiniciproducens MBEL55E, from bovine rumen”,
Applied microbiology and biotechnology, 58(5), 663-668.
Lee, P.C., Lee, S., Hong, S.H., Chang, H.N. and Park, S.C., 2003. “Biological conversion of wood
hydrolysate to succinic acid by Anaerobiospirillum succiniciproducens”, Bio. Ltrs., 25, 111-114.
Lee, S.Y., Kim, J.M., Song, H., Lee, J.W., Kim, T.Y. and Jang, Y.S., 2008. “From genome sequence
to integrated bioprocess for succinic acid production by Mannheimia succiniciproducens”,
Applied microbiology and biotechnology, 79(1), 11-22.
Lee, S.Y., Lee, J.W., Choi, S. and Yi, J., Korea Advanced Institute of Science and Tech KAIST, 2014.
“Mutant microorganism producing succinic acid simultaneously using sucrose and glycerol,
and method for preparing succinic acid using same”, U.S. Patent 8,691,516B2.
León, J.A. and Fontalvo, J., 2018. “Tools for the Design of Hybrid Distillation–Pervaporation
Columns in a Single Unit: Hybrid Rectifying–Pervaporation Section”, Industrial & Engineering
Chemistry Research, 57(35), 11970-11980.
Page 192
References
172
Li, J., Demirel, S.E. and Hasan, M.F., 2017. “Simultaneous process synthesis and process
intensification using building blocks”, Computer Aided Chemical Engineering, 40, 1171-1176.
Li, L.J., Zhou, R.J., Dong, H.G. and Grossmann, I.E., 2011. “Separation network design with mass
and energy separating agents”, Computers & Chemical Engineering, 35(10), 2005-2016.
Li, Q., Siles, J.A. and Thompson, I.P., 2010. “Succinic acid production from orange peel and wheat
straw by batch fermentations of Fibrobacter succinogenes S85”, Applied microbiology and
biotechnology, 88(3), 671-678.
Litsanov, B., Brocker, M. and Bott, M., 2012. “Towards homosuccinate fermentation: metabolic
engineering of Corynebacterium glutamicum for anaerobic succinate production from glucose
and formate”, Applied and environmental microbiology, pp.AEM-07790.
Lu, M.D. & Motard, R.L., 1985. “Computer-Aided Total Flowsheet Synthesis”, Computers &
Chemical Engineering, 9(5), 431–445.
Lutze, P., Babi, D. K., Woodley, J. M. & Gani, R., 2013. “Phenomena based methodology for
process synthesis incorporating process intensification”, Industrial & Engineering Chemistry
Research, 52(22), 7127-7144.
Lutze, P., 2011. “An innovative synthesis methodology for process intensification”, DTU Chemical
Engineering.
McKinlay, J.B., Vieille, C. and Zeikus, J.G., 2007. “Prospects for a bio-based succinate industry”,
Applied microbiology and biotechnology, 76(4), 727-740.
Meidanshahi, V., Bahmanpour, A.M., Iranshahi, D. and Rahimpour, M.R., 2011. “Theoretical
investigation of aromatics production enhancement in thermal coupling of naphtha reforming
and hydrodealkylation of toluene”, Chem. Engg. and Proc.: Process Inten., 50(9), 893-903.
Muller, M., and Hubsch, U., 2005. “Dimethylether - In Ullmann’s encyclopedia of industrial
chemistry”, 7th ed, Weinheim: Wiley–VCH.
Murthy Konda, N.V.S.N., Rangaiah, G.P. and Lim, D.K., 2006. “Optimal process design and
effective plantwide control of industrial processes by a simulation-based heuristic approach”,
Industrial & engineering chemistry research, 45(17), 5955-5970.
Noorman, H. J., van Winden, W., Heijnen, J. J. and van der Lans, R. G. J. M., 2018. “Intensified
Fermentation Processes and Equipment”, Intensification of Biobased Processes, 16, 1-41.
Papalexandri, K.P. and Pistikopoulos, E.N., 1996. “Generalized modular representation
framework for process synthesis”, AIChE Journal, 42(4), 1010-1032.
Page 193
References
173
Okino, S., Inui, M. and Yukawa, H., 2005. “Production of organic acids by Corynebacterium
glutamicum under oxygen deprivation”, Applied microbiology and biotechnology, 68(4),
pp.475-480.
Oliveira, F.S., Araújo, J.M., Ferreira, R., Rebelo, L.P.N. and Marrucho, I.M., 2012. “Extraction of
L-lactic, L-malic, and succinic acids using phosphonium-based ionic liquids”, Separation and
purification technology, 85, pp.137-146.
Ozokwelu D. 2014. “High efficiency modular chemical processes (HEMCP)”, Washington, DC:
US Department of Energy. 12. https://energy.gov/sites/prod/files/2014/10/f18/hemcp-topic-
overview.pdf (accessed 24th November, 2017)
Peschel, A., Freund, H. and Sundmacher, K., 2010. “Methodology for the design of optimal
chemical reactors based on the concept of elementary process functions”, Industrial &
Engineering Chemistry Research, 49(21), 10535-10548.
Peschel, A., Jorke, A., Freund, H. and Sundmacher, K., 2012. “Model-based development of
optimal reaction concepts for plant wide process intensification”, Computer Aided Chemical
Engineering, 31, 150-154.
Peschel, A., Karst, F., Freund, H. and Sundmacher, K., 2011. “Analysis and optimal design of an
ethylene oxide reactor”, Chemical engineering science, 66(24), 6453-6469.
Pirola, C., Galli, F., Manenti, F., Corbetta, M. and Bianchi, C.L., 2014. “Simulation and related
experimental validation of acetic acid/water distillation using p-xylene as entrainer”,
Industrial & Engineering Chemistry Research, 53(46), 18063-18070.
Portha, J.F., Falk, L. and Commenge, J.M., 2014. “Local and global process intensification”,
Chemical Engineering and Processing: Process Intensification, 84, 1-13.
PRO/II, https://sw.aveva.com/engineer-procure-construct/engineering-process-design/pro-ii
(accessed 08 November, 2018).
Quaglia, A., Sarup, B., Sin, G. and Gani, R., 2012. “Integrated business and engineering framework
for synthesis and design of enterprise-wide processing networks”, Computers & Chemical
Engineering, 38, 213-223.
Quaglia, A., Sarup, B., Sin, G. and Gani, R., 2013. “Design of a generic and flexible data structure
for efficient formulation of large scale network problems”,Computer Aided Chemical
Engineering, 32, 661-666.
Page 194
References
174
Raab, A.M., Gebhardt, G., Bolotina, N., Weuster-Botz, D. and Lang, C., 2010. “Metabolic
engineering of Saccharomyces cerevisiae for the biotechnological production of succinic acid”,
Metabolic engineering, 12(6), 518-525.
Ramapriya, G.M., Tawarmalani, M., Agrawal, R., 2014. “Thermal coupling links to liquidonly
transfer streams: a path for new dividing wall columns”, AIChE Journal 60(8), 2949–2961.
Rao, A.V., Hegde, N.D. and Hirashima, H., 2007. “Absorption and desorption of organic liquids
in elastic superhydrophobic silica aerogels”, Journal of colloid and interface science, 305(1),
124-132.
Reay, D., Ramshaw, C., Harvey, A., 2008. “Process Intensification: Engineering for Efficiency,
Sustainability and Flexibility”, Butterworth-Heinemann, Oxford. ISBN 9780750689410.
Rigopoulos, S. and Linke, P., 2002. “Systematic development of optimal activated sludge process
designs”, Computers & Chemical Engineering, 26(4-5), 585-597.
Rong, B. G., Kolehmainen, E. & Turunen, I., 2008. “Methodology of conceptual process synthesis
for process intensification”, Computer Aided Chemical Engineering, 25, 283-288.
Rong, B.G., Kolehmainen, E., Turunen, I. and Hurme, M., 2004. “Phenomena-based
methodology for process intensification”, Computer Aided Chemical Engineering, 18, 481-486.
Rush, B.J. and Fosmer, A.M., BioAmber Inc, 2014. “Methods for succinate production”, U.S.
Patent 0363862A1.
Saengwirun, P., 2011. “ECON: A software for cost calculation and economic analysis”, The
Petroleum and Petrochemical College, Chulalongkorn University, Bangkok, Thailand.
Sánchez, A.M., Bennett, G.N. and San, K.Y., 2005. “Novel pathway engineering design of the
anaerobic central metabolic pathway in Escherichia coli to increase succinate yield and
productivity”, Metabolic engineering, 7(3), 229-239.
Seader, J.D. & Westerberg, A.W., 1977. “A combined heuristic and evolutionary strategy for
synthesis of simple separation sequences”, AIChE Journal, 23(1971), 951–954.
Scholten, E., Renz, T. and Thomas, J., 2009. “Continuous cultivation approach for fermentative
succinic acid production from crude glycerol by B. succiniciproducens DD1”, Biotechnology
letters, 31(12), 1947.
Schroder, H., Haefner, S., Von Abendroth, G., Hollmann, R., Raddatz, A., Ernst, H. and Gurski,
H., BASF SE, 2014. “Microbial succinic acid producers and purification of succinic acid”, U.S.
Patent 8,673,598.
Page 195
References
175
Seader, J.D., Seider, W.D. and Lewin, D.R., 2004. “Product and process design principles:
synthesis, analysis, and evaluation”, Wiley.
Seifert, T., Sievers, S., Bramsiepe, C. & Schembecker, G., 2012. “Small scale, modular and
continuous: a new approach in plant design”, Chemical Engineering Proc 52:140–150.
Sempuga, B. C., Hausberger, B., Patel, B., Hildebrandt, D. & Glasser, D., 2010. “Classification of
chemical processes: a graphical approach to process synthesis to improve reactive process
work efficiency”, Industrial & Engineering Chemistry Research, 49(17), 8227-8237.
Shah, M., Kiss, A.A., Zondervan, E. and de Haan, A.B., 2012. “A systematic framework for the
feasibility and technical evaluation of reactive distillation processes”, Chemical Engineering
and Processing: Process Intensification, 60, 55-64.
Siirola, J. J., 1996. “Strategic process synthesis: Advances in the hierarchical approach”,
Computers & Chemical Engineering, 20, S1637–S1643. doi:10.1016/0098-1354(96)85982-5.
Siirola, J. J., Powers, G. J., & Rudd, D. F., 1971. “Synthesis of system designs: III. Toward a process
concept generator”, AIChE Journal, 17(3), 677–682.
Smith, K. B. & Mackley, M. R., 2006. “An experimental investigation into the scale-up of
oscillatory flow mixing in baffled tubes”, Chemical Eng. Research and Design, 84, 1001-1011.
Song, H. and Lee, S.Y., 2006. “Production of succinic acid by bacterial fermentation”, Enzyme
and microbial technology, 39(3), 352-361.
Soper, J.G., Schultz, M. and Binder, T.P., Archer Daniels Midland Co, 2013. “Purification of
succinic acid”, WO2013/169447A1.
Steffens, M.A., Fraga, E.S. and Bogle, I.D.L., 2000. “Synthesis of bioprocesses using physical
properties data”, Biotechnology and bioengineering, 68(2), 218-230.
Stephanopoulos, G. & Westerberg, A.W., 1976. “Studies in process synthesis—II”, Chemical
Engineering Science, 31, 195–204.
Sundaram, S., 2015. Biorefineries and chemical processes: design, integration and sustainability
analysis. Green Processing and Synthesis, 4(1), 65-66.
Ycharts indicative pricing, https://ycharts.com/indicators/us_sugar_futures_contract_price
(accessed in 2017).
Tian, Y. and Pistikopoulos, E.N., 2018. “Synthesis of Operable Process Intensification Systems—
Steady-State Design with Safety and Operability Considerations”, Industrial & Engineering
Chemistry Research, 58(15), 6049-6068.
Page 196
References
176
Tian, Y., Demirel, S.E., Hasan, M.F. and Pistikopoulos, E.N., 2018. “An overview of process
systems engineering approaches for process intensification: State of the art”, Chemical
Engineering and Processing-Process Intensification, 133, 160-210.
Tula, A.K., 2017. “Computer-Aided Sustainable Process Synthesis-Design and Analysis”,
Technical University of Denmark. Retrieved from https://orbit.dtu.dk/en/publications/
computeraided-sustainable-process-synthesisdesign-and-analysis(f90857ef-0793-45d0-adc3-
c604d9e15a26).html
Tula, A.K., Babi, D.K., Bottlaender, J., Eden, M.R. and Gani, R., 2017. “A computer-aided software-
tool for sustainable process synthesis-intensification”, Computers & Chemical Engineering,
105, 74-95.
Tula, A.K., Befort, B., Garg, N., Camarda, K.V. and Gani, R., 2017, “Sustainable process design &
analysis of hybrid separations”, Computers and Chemical Engineering, 105, 96-104.
Tula, A.K., Eden, M.R. and Gani, R., 2014. “Process synthesis, design and analysis using process-
group contribution method”, In Computer Aided Chemical Engineering, 34, 453-458.
Tula, A.K., Eden, M.R. and Gani, R., 2015. “Process synthesis, design and analysis using a process-
group contribution method”, Computers & Chemical Engineering, 81, 245-259.
Tula, A.K., Gani, R. and Eden, M.R., 2017. “New Method and Software for Computer-Aided
Flowsheet Design and Analysis”, Computer Aided Chemical Engineering, 40, 649-654.
Välimäki C., Towards sustainable future, https://www.sustainablebrands.com/news_and_views/
chemistry_materials_packaging/christina_v%C3%A4lim%C3%A4ki/why_sustainability_futur
e_chemical (accessed 10 October, 2018).
Van Baelen, D., Van der Bruggen, B., Van den Dungen, K., Degrève, J. and Vandecasteele, C.,
2005. ”Pervaporation of water–alcohol mixtures and acetic acid–water mixtures”, Chemical
Engineering Science, 60(6), 1583-1590.
Van Gerven, T. & Stankiewicz, A., 2009. “Structure, energy, synergy, time: The fundamentals of
process intensification”, Industrial & engineering chemistry research, 48(5), 2465-2474.
Vogel, H.C. and Todaro, C.M., 1996. “Fermentation and biochemical engineering handbook:
principles, process design and equipment”, William Andrew.
Van De Graaf, M.J., Vallianpoer, F., Fiey, G., Delattre, L. and Schulten, E.A.M., Roquette Freres
and DSM IP Assets BV, 2012. “Process for the crystallization of succinic acid”, U.S. Patent
2012/0238722A1.
Page 197
References
177
Vaswani, S., 2010. “Bio-based succinic acid. California: Sri Consulting”, Review, (14).
Vemuri, G.N., Eiteman, M.A. and Altman, E., 2002. “Effects of growth mode and pyruvate
carboxylase on succinic acid production by metabolically engineered strains of Escherichia
coli”, Applied and Environmental Microbiology, 68(4), 1715-1727.
Wang, C., Ming, W., Yan, D., Zhang, C., Yang, M., Liu, Y., Zhang, Y., Guo, B., Wan, Y. and Xing,
J., 2014. “Novel membrane-based biotechnological alternative process for succinic acid
production and chemical synthesis of bio-based poly (butylene succinate)”, Bioresource
technology, 156, 6-13.
Wightman, E. P., Trivelli, A.P.H. & Sheppard, S. E., 1925. “Intensification of the latent image on
photographic plates intensification”, Journal of the Franklin Institute, 200, 335.
Yedur, S., Berglund, K.A. and Dunuwila, D.D., Applied Carbochemicals and Michigan State
University, 2001. “Succinic acid production and purification”, U.S. Patent 6,265,190.
Yee, T.F. & Grossmann, I.E., 1990. “Simultaneous optimization models for heat integration—II.
Heat exchanger network synthesis”, Computers & Chemical Engineering, 14, 1165–1184.
Yuzbashev, T.V., Yuzbasheva, E.Y., Sobolevskaya, T.I., Laptev, I.A., Vybornaya, T.V., Larina, A.S.,
Matsui, K., Fukui, K. and Sineoky, S.P., 2010. “Production of succinic acid at low pH by a
recombinant strain of the aerobic yeast Yarrowia lipolytica”, Biotechnology and
bioengineering, 107(4), 673-682.
Zhang, J., Liu, H. and Jiang, L., 2017. “Membrane-based strategy for efficient ionic liquids/water
separation assisted by superwettability”, Advanced Functional Materials, 27(20), 1606544.
Zhang, L., Zhang, H.T., Ying, W.Y. and Fang, D.Y., 2011. “Intrinsic kinetics of methanol
dehydration over Al2O3 catalyst”, Engineering and Technology, 59, 1538-1543.
Zondervan, E., Nawaz, M., de Haan, A.B., Woodley, J.M. and Gani, R., 2011. “Optimal design of a
multi-product biorefinery system”, Computers & Chemical Engineering, 35(9), 1752-1766.
Page 199
References
179
Appendices
Appendix A: Process hotspots identification
A.1: Indicative list for process hotspots identification based on economic,
sustainability and life cycle analysis (adapted from Babi, 2014; Tula, 2016)
Indicator values Base Case property
Reason Identified Process hot-spot
- Raw material recycle/cost - Material value added
Un-reacted raw materials
Equilibrium reaction
- Activation problems - Limiting equilibrium/raw material loss - Contact problems of raw materials/limited mass transfer - Limited heat transfer
- Utility cost - Energy waste cost - CO2 equivalent
Heat of reaction Exothermic reaction - Highly exothermic reaction
- Utility cost - Energy waste cost - CO2 equivalent
Heat of reaction Endothermic reaction - Highly Endothermic reaction
- Utility cost - Capital cost
Operating conditions
Temperature and pressure operating window for the reactor
- Explosive mixture - Product degradation by temperature
- Product sale Formation of byproduct(s)
number of desired products plus number of undesired products
- Formation of undesired side-products
- Utility cost - Material value added - Energy waste cost - CO2 equivalent
Un-reacted raw materials and products recovery
Presence of azeotrope(s), High energy usage heating and/or cooling
- Azeotrope - Difficult separation - Low driving force - High energy consumption and/or demand
-Insufficient purity Presence of other compounds and product recovery
Presence of azeotrope(s), eutectic point
- Azeotrope - Difficult separation - Low driving force
Page 200
Ap
pen
dic
es
18
0
Ap
pe
nd
ix B
: D
esi
gn
ta
rge
ts i
de
nti
fica
tio
n
B.1
: A
n i
nd
ica
tiv
e l
ist
for
de
sig
n t
arg
ets
ba
sed
on
pro
cess
ho
tsp
ots
(a
da
pte
d f
rom
Ba
bi,
20
14;
Tu
la,
20
16)
Pro
cess
ho
tsp
ot/
De
sig
n t
arg
et
Act
ivat
ion
p
rob
lem
s L
imit
ing
eq
uil
ibri
um
L
imit
ed m
ass
tran
sfer
L
imit
ed h
eat
tran
sfer
Fo
rmat
ion
of
un
des
ired
sid
e-p
rod
uct
s A
zeo
tro
pe
Dif
ficu
lt s
epar
atio
n d
ue
to l
ow
dri
vin
g f
orc
e H
igh
en
erg
y co
nsu
mp
tio
n/d
eman
d
Incr
ease
raw
mat
eria
l co
nve
rsio
n
* *
* *
*
* *
Red
uce
raw
mat
eria
l lo
ss
* *
* *
* *
* *
Red
uce
pro
du
ct l
oss
*
* *
*
Red
uce
en
erg
y co
nsu
mp
tio
n
*
*
* *
Incr
ease
pu
rity
*
* *
*
Red
uce
uti
lity
co
st
*
*
* *
Un
it o
per
atio
ns
red
uct
ion
*
* *
* *
* *
*
Imp
rove
men
t in
L
CA
/su
stai
nab
ilit
y in
dic
ato
rs
* *
* *
* *
* *
Pro
du
ct p
uri
ty
* *
* *
* *
* *
Pro
du
ctio
n t
arg
et
* *
* *
* *
* *
Was
te m
inim
izat
ion
*
* *
* *
* *
*
Page 201
Ap
pen
dic
es
18
1
Ap
pe
nd
ix C
: K
no
wle
dg
e b
ase
s (K
B)
C.1
: T
ran
sla
tio
n o
f u
nit
-op
era
tio
ns
to t
ask
an
d p
he
no
me
na
(K
B2
.1)
(ex
pa
nd
ed
fro
m L
utz
e,
20
12 a
nd
Ba
bi,
20
14)
Inte
nsi
fie
d E
qu
ipm
en
t F
ee
d P
ha
se
Ta
sk
PB
Bs
Cre
ate
d o
r a
dd
ed
ph
ase
M
SA
-Y
/N
Se
pa
rati
ng
ag
en
t
Bat
ch r
eact
or
S,
V a
nd
/or
L
Rea
ctio
n
M,
2p
hM
(tw
o p
has
es),
R,
ES
(C)
(exo
ther
mic
), E
S(H
)(e
nd
oth
erm
ic)
-Y
/NL
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Sem
i-b
atch
rea
cto
r S
, V
an
d/o
r L
R
eact
ion
M
, 2
ph
M(t
wo
ph
ases
), R
, E
S(C
) (e
xoth
erm
ic),
ES
(H )
(en
do
ther
mic
) -
Y/N
Liq
uid
so
lven
t (M
SA
) an
d
ener
gy
tran
sfer
(E
SA
)
CS
TR
L
R
eact
ion
M
, R
, E
S(C
) (e
xoth
erm
ic),
ES
(H )
(en
do
ther
mic
) -
Y/N
Liq
uid
so
lven
t (M
SA
) an
d
ener
gy
tran
sfer
(E
SA
)
Tu
bu
lar
Rea
cto
r (P
FR
) V
R
eact
ion
M
, R
, E
S(C
) (e
xoth
erm
ic),
ES
(H )
(en
do
ther
mic
) -
N
En
erg
y tr
ansf
er (
ES
A)
Pac
k-b
ed r
eact
or
S a
nd
/or
V
Rea
ctio
n
M,
2p
hM
(tw
o p
has
es),
R,
ES
(C)
(exo
ther
mic
), E
S(H
)(e
nd
oth
erm
ic)
-N
E
ner
gy
tran
sfer
(E
SA
)
Par
tial
co
nd
ensa
tio
n o
r va
po
riza
tio
n
V a
nd
/or
L
Sep
arat
ion
M
, P
T(V
L),
PS
(VL
), E
S(H
)/E
S(C
) V
or
L
N
En
erg
y tr
ansf
er (
ES
A)
Fla
sh v
apo
riza
tio
n
L
Sep
arat
ion
M
, P
T(V
L),
PS
(VL
) V
N
P
ress
ure
red
uct
ion
Dis
till
atio
n
V a
nd
/or
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(H
) V
an
d L
N
H
eat
tran
sfer
(E
SA
) an
d
som
etim
es w
ork
tra
nsf
er
Ext
ract
ive
dis
till
atio
n
V a
nd
/or
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(H
) V
an
d L
Y
L
iqu
id s
olv
ent
(MS
A)
and
h
eat
tran
sfer
(E
SA
)
Reb
oil
ed a
bso
rpti
on
V
an
d/o
r L
S
epar
atio
n
M,
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L),
ES
(H)
V a
nd
L
Y
Liq
uid
ab
sorb
ent
(MS
A)
and
hea
t tr
ansf
er (
ES
A)
Gas
Ab
sorp
tio
n
V a
nd
/or
L
Sep
arat
ion
M
, P
T(V
L),
PS
(VL
) L
iqu
id
Y
Liq
uid
ab
sorb
ent
(MS
A)
Str
ipp
ing
L
S
epar
atio
n
M,
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L)
V
Y
Str
ipp
ing
vap
or
(MS
A)
Ste
am d
isti
llat
ion
V
an
d/o
r L
S
epar
atio
n
M,
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L),
ES
(C)
V a
nd
/or
L
Y
Str
ipp
ing
vap
or
(MS
A)
and
hea
t tr
ansf
er (
ES
A)
Reb
oil
ed s
trip
pin
g
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(H
) V
N
H
eat
tran
sfer
(E
SA
)
Aze
otr
op
ic d
isti
llat
ion
V
an
d/o
r L
S
epar
atio
n
M,
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L),
PC
(LL
), P
S(L
L),
ES
(C),
ES
(H)
V a
nd
L
Y
Liq
uid
en
trai
ner
(M
SA)
and
hea
t tr
ansf
er (
ES
A)
Page 202
Ap
pen
dic
es
18
2
Liq
uid
–li
qu
id e
xtra
ctio
n
L
Sep
arat
ion
M
, P
C(L
L),
PT
(LL
), P
S(L
L)
L
Y
Liq
uid
so
lven
t (M
SA
)
Liq
uid
–li
qu
id e
xtra
ctio
n (
two
so
lven
t)
L
Sep
arat
ion
M
, P
C(L
L),
PT
(LL
), P
S(L
L)
L
Y
Tw
o l
iqu
id s
olv
ents
(M
SA
1 an
d M
SA2
)
Dry
ing
L
/S
Sep
arat
ion
M
, P
C(L
S),
PT
(VL
), P
S(V
L),
ES
(H)
V
Y
Gas
(M
SA
) an
d/o
r h
eat
tran
sfer
(E
SA
)
Eva
po
rati
on
L
S
epar
atio
n
M,
PT
(VL
), P
S(V
L),
ES(
H)
V
N
En
erg
y tr
ansf
er (
ES
A)
Cry
stal
liza
tio
n
L
Sep
arat
ion
M
, P
T(L
S),
PS
(LS
), E
S(H
) S
an
d V
N
E
ner
gy
tran
sfer
(E
SA
)
L
Sep
arat
ion
M
, P
T(L
S),
PS
(LS
), E
S(C
) S
N
E
ner
gy
tran
sfer
(E
SA
)
Des
ub
lim
atio
n
V
Sep
arat
ion
M
, P
T(V
S),
PS
(VS
), E
S(C
) S
N
E
ner
gy
tran
sfer
(E
SA
)
Lea
chin
g (
liq
uid
–so
lid
ext
ract
ion
) S
S
epar
atio
n
M,
2p
hM
, P
C(L
S),
PT
(LS
), P
S(L
S)
L
Y
Liq
uid
so
lven
t (M
SA
)
Div
idin
g W
all
Co
lum
n
V a
nd
/or
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(H
) V
an
d L
N
H
eat
tran
sfer
(E
SA
) an
d
som
etim
es w
ork
tra
nsf
er
Dec
ante
r L
S
epar
atio
n
M,
PC
(LL
), P
S(L
L)
L
N
-
Su
per
crit
ical
Ext
ract
ion
L
S
epar
atio
n
M,
PC
(LL
), P
T(L
L),
PS
(LL
), E
S(C
), E
S(H
) L
Y
S
up
ercr
itic
al a
bso
rben
t (M
SA
)
Mem
bra
ne-
Per
vap
ora
tio
n
V a
nd
L
Sep
arat
ion
M
, P
T(M
VL
), P
S(V
L)
L
N
En
erg
y tr
ansf
er (
ES
A)
Mem
bra
ne-
Vap
or-
per
mea
tio
n
V
Sep
arat
ion
M
, P
T(M
VV
), P
S(V
V)
V
N
En
erg
y tr
ansf
er (
ES
A)
Mem
bra
ne
(Per
vap
ora
tio
n)
R
eact
or
V a
nd
L
Rea
ctio
n+
S
epar
atio
n
M,
2p
hM
(tw
o p
has
es),
R,
PT
(MV
L)
, E
S(C
)(ex
oth
erm
ic),
E
S(H
)(en
do
ther
mic
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Rea
ctiv
e D
isti
llat
ion
V
an
d/o
r L
R
eact
ion
+
Sep
arat
ion
M
, 2
ph
M,
R,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(H
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Rea
ctiv
e D
ivid
ing
Wal
l C
olu
mn
V
an
d/o
r L
R
eact
ion
+
Sep
arat
ion
M
, 2
ph
M,
R,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(H
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Div
idin
g w
all
colu
mn
V
an
d/o
r L
S
epar
atio
n
M,
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L),
ES
(C),
ES
(H)
V a
nd
L
N
En
erg
y tr
ansf
er (
ES
A)
Rea
ctiv
e d
isti
llat
ion
V
an
d/o
r L
R
eact
ion
+
Sep
arat
ion
M
, 2
ph
M,
R,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(H
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Mem
bra
ne-
reac
tive
dis
till
atio
n
V a
nd
/or
L
Rea
ctio
n +
S
epar
atio
n
M,
2p
hM
, R
, P
C(V
L),
PT
(VL
), P
S(V
L),
PT
(MV
L/M
VV
/ML
L),
P
S(L
L/V
V),
E
S(C
), E
S(H
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Page 203
Ap
pen
dic
es
18
3
Mic
row
ave
dry
ing
S a
nd
L
Sep
arat
ion
M
, P
C(L
S),
PT
(VL
), P
S(V
L),
ES
(D)
V
N
En
erg
y tr
ansf
er (
ES
A)
Sta
tic
mix
er r
eact
ors
fo
r co
nti
nu
ou
s re
acti
on
s L
an
d/o
r S
an
d/o
r V
R
eact
ion
M
, 2
ph
M ,
R,
ES
(C)(
exo
ther
mic
), E
S(H
)(en
do
ther
mic
) -
Y/N
L
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Pu
lsed
co
mp
ress
ion
rea
cto
r V
R
eact
ion
M
, R
, E
S(D
) -
Y/N
L
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Cen
trif
ug
al l
iqu
id-l
iqu
id
con
tact
ors
L
iqu
id
Sep
arat
ion
M
, P
C(L
L),
PS
(LL
), E
S(D
) -
N
-
Ph
oto
chem
ical
rea
cto
r L
an
d/o
r S
an
d/o
r V
R
eact
ion
M
, 2
ph
M(t
wo
ph
ases
), R
, E
S(D
), E
S(C
)(ex
oth
erm
ic),
E
S(H
)(en
do
ther
mic
) -
Y/N
L
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Rea
ctiv
e ab
sorp
tio
n
V
Rea
ctio
n +
S
epar
atio
n
M,
R,
PT
(VL
), P
S(V
L)
L
Y
Liq
uid
ab
sorb
ent
(MS
A)
Mem
bra
ne
crys
tall
izat
ion
L
S
epar
atio
n
M,
PT
(LS
), P
S(L
S),
PT
(ML
L),
PS
(LL
,VV
), E
S(C
) S
N
E
ner
gy
tran
sfer
(E
SA
)
M,
PC
(LS
), P
T(L
S),
PS
(LS
), P
T(M
VL
/ML
L),
PC
(VL
), P
T(V
L),
P
S(L
L,V
V),
ES
(H)
S a
nd
V
N
En
erg
y tr
ansf
er (
ES
A)
Mem
bra
ne
dis
till
atio
n
V a
nd
/or
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), P
T(M
VL
/MV
V/M
LL
),
PS
(LL
,VV
), E
S(C
), E
S(H
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Ult
raso
un
d r
eact
or
L a
nd
/or
S
and
/or
V
Rea
ctio
n
M,
2p
hM
(tw
o p
has
es),
R,
ES
(D),
ES
(C)(
exo
ther
mic
),
ES
(H)(
end
oth
erm
ic)
- Y
/N
Liq
uid
so
lven
t (M
SA
) an
d
ener
gy
tran
sfer
(E
SA
)
So
no
chem
ical
rea
cto
r L
an
d/o
r S
an
d/o
r V
R
eact
ion
M
, 2
ph
M(t
wo
ph
ases
), R
, E
S(D
), E
S(C
)(ex
oth
erm
ic),
E
S(H
)(en
do
ther
mic
) -
Y/N
L
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Ult
raso
un
d e
nh
ance
d
crys
tall
izat
ion
L
S
epar
atio
n
M,
PT
(LS
), P
S(L
S),
ES
(D)
S o
r V
N
E
ner
gy
tran
sfer
(E
SA
)
Pu
lse
com
bu
stio
n d
ryin
g
S a
nd
L
Sep
arat
ion
M
, P
T(V
L),
PS
(VL
), E
S(D
) V
N
E
ner
gy
tran
sfer
(E
SA
)
Ad
sorp
tive
dis
till
atio
n
V a
nd
/or
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), P
C(L
S),
PS
(LS)
, E
S(C
), E
S(H
) S
Y
S
oli
d a
gen
t (M
SA
)
Rea
ctiv
e ex
trac
tio
n c
olu
mn
s L
S
epar
atio
n
M,
R,
PC
(LL
), P
S(L
L)
Liq
uid
Y
L
iqu
id s
olv
ent
(MS
A)
Div
ided
wal
l co
lum
n (
extr
acti
ve)
V a
nd
/or
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(H
) V
an
d L
Y
L
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Mic
row
ave-
assi
sted
dis
till
atio
n
V a
nd
/or
L
Sep
arat
ion
M
, 2
ph
M,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(D
), E
S(D
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Mic
row
ave-
assi
sted
rea
ctiv
e d
isti
llat
ion
V
an
d/o
r L
R
eact
ion
+
Sep
arat
ion
M
, 2
ph
M,
R,
PC
(VL
), P
T(V
L),
PS
(VL
), E
S(C
), E
S(D
), E
S(D
) V
an
d L
N
E
ner
gy
tran
sfer
(E
SA
)
Mem
bra
ne
reac
tor
L a
nd
/or
S
and
/or
V
Rea
ctio
n +
S
epar
atio
n
M,
2p
hM
(tw
o p
has
es),
R,
PT
(MV
L/M
VV
/ML
L),
PS
(LL
,VV
, V
L)
- N
E
ner
gy
tran
sfer
(E
SA
)
Page 204
Ap
pen
dic
es
18
4
Fil
trat
ion
or
Cen
trif
ug
e L
an
d/o
r S
Sep
arat
ion
M
, P
C(L
S),
PS
(LS
) -
N
-
Liq
uid
Mem
bra
ne-
Sep
arat
ion
(eg
R
ever
se o
r fo
rwar
d o
smo
ssis
) L
S
epar
atio
n
M,
PT
(ML
L),
PS
(LL
) -
N
-
Ad
sorp
tio
n
V o
r L
S
epar
atio
n
M,
PC
(LS
/VS
), P
S(L
S/V
S)
S
Y
So
lid
ag
ent
(MS
A)
Ad
sorp
tio
n
V
Sep
arat
ion
M
, P
C(V
L),
PS
(VL
) L
Y
L
iqu
id a
gen
t (M
SA
)
Mic
row
ave
reac
tor
L a
nd
/or
S
and
/or
V
Rea
ctio
n
M,
2p
hM
(tw
o p
has
es),
R,
ES
(D)
, E
S(C
)(ex
oth
erm
ic),
E
S(H
)(en
do
ther
mic
) -
Y/N
L
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Ult
raso
un
d r
eact
or
L a
nd
/or
S
and
/or
V
Rea
ctio
n
M,
2p
hM
(tw
o p
has
es),
R,
ES
(D)
, E
S(C
)(ex
oth
erm
ic),
E
S(H
)(en
do
ther
mic
) -
Y/N
L
iqu
id s
olv
ent
(MS
A)
and
en
erg
y tr
ansf
er (
ES
A)
Mel
ter
S
Sep
arat
ion
P
T(L
S),
PS
(LS
) L
N
-
Page 205
Ap
pen
dic
es
18
5
C.2
: T
ran
sla
tio
n o
f p
roce
ss h
ots
po
ts t
o p
rin
cip
le P
BB
s (K
B2
.2)
(ex
pa
nd
ed
fro
m L
utz
e,
20
12 a
nd
Ba
bi,
20
14)
Sr.
No
. P
roce
ss H
ots
po
t M
ain
ta
sk
Pro
pe
rty
/Bin
ary
Ra
tio
A
lte
rna
tiv
e
Ta
sk
MS
A-
Y/N
A
dd
itio
na
l in
form
ati
on
P
BB
1 A
ctiv
atio
n p
rob
lem
s R
eact
ion
C
alcu
late
ΔG
rxn
R
eact
ion
N
U
se o
f ca
taly
st
2p
hM
(tw
o p
has
es),
E
S(H
)
R
eact
ion
C
alcu
late
ΔG
rxn
R
eact
ion
N
U
se o
f d
irec
t en
erg
y so
urc
e 2
ph
M (
two
ph
ases
),
ES
(H)
2
Lim
itin
g
equ
ilib
riu
m/r
aw
mat
eria
l lo
ss
Rea
ctio
n
So
lub
ilit
y p
aram
eter
S
epar
atio
n
Y
Eq
uil
ibri
um
sh
ift
PC
(LL
), P
T(L
L),
PS
(LL
)
R
eact
ion
V
apo
r p
ress
ure
, h
eat
of
vap
ori
zati
on
, b
oil
ing
po
int
Sep
arat
ion
N
E
qu
ilib
riu
m s
hif
t 2
ph
M,
PC
(VL
), P
T(V
L),
P
S(V
L),
ES
(C),
ES
(H)
R
eact
ion
M
ola
r vo
lum
e, s
olu
bil
ity
par
amet
er
Sep
arat
ion
N
E
qu
ilib
riu
m s
hif
t P
T(M
VL
), P
S(V
L)
R
eact
ion
V
an d
er W
aals
vo
lum
e, c
riti
cal
tem
p
Sep
arat
ion
N
E
qu
ilib
riu
m s
hif
t P
T(M
VV
), P
S(V
V)
R
eact
ion
M
ole
cula
r w
eig
ht,
mo
lecu
lar
dia
met
er
Sep
arat
ion
N
E
qu
ilib
riu
m s
hif
t P
C(L
S),
PS
(LS
)
R
eact
ion
S
olu
bil
ity
par
amet
er,
rad
ius
of
gyr
atio
n,
mo
lar
volu
me
Sep
arat
ion
N
E
qu
ilib
riu
m s
hif
t P
T(M
LL
), P
S(L
L)
3 H
igh
ly e
nd
oth
erm
ic
Rea
ctio
n
Cal
cula
te Δ
Hrx
n
Rea
ctio
n
N
Hea
tin
g
ES
(H)
R
eact
ion
C
alcu
late
ΔH
rxn
R
eact
ion
N
H
eati
ng
E
S(D
)
4
Hig
hly
exo
ther
mic
R
eact
ion
C
alcu
late
ΔH
rxn
R
eact
ion
N
C
oo
lin
g E
S(C
)
R
eact
ion
C
alcu
late
ΔH
rxn
R
eact
ion
N
A
lter
nat
ive
coo
lin
g s
ou
rce
ES
(D)
5
Fo
rmat
ion
of
un
des
ired
sid
e-p
rod
uct
s
Rea
ctio
n
- R
eact
ion
N
R
eact
ion
fo
r re
acti
ng
aw
ay s
ide
pro
du
cts
R
R
eact
ion
S
olu
bil
ity
par
amet
er
Sep
arat
ion
Y
S
epar
atio
n o
f si
de-
pro
du
cts
PC
(LL
), P
T(L
L),
PS
(LL
)
R
eact
ion
V
apo
r p
ress
ure
, h
eat
of
vap
ori
zati
on
, b
oil
ing
po
int
Sep
arat
ion
N
S
epar
atio
n o
f si
de-
pro
du
cts
2p
hM
, P
C(V
L),
PT
(VL
),
PS
(VL
), E
S(C
), E
S(H
)
R
eact
ion
M
ola
r vo
lum
e, s
olu
bil
ity
par
amet
er
Sep
arat
ion
N
S
epar
atio
n o
f si
de-
pro
du
cts
PT
(MV
L),
PS
(VL
)
R
eact
ion
V
an d
er W
aals
vo
lum
e, c
riti
cal
tem
p
Sep
arat
ion
N
S
epar
atio
n o
f si
de-
pro
du
cts
PT
(MV
V),
PS
(VV
)
R
eact
ion
S
olu
bil
ity
par
amet
er,
rad
ius
of
gyr
atio
n,
mo
lar
volu
me
Sep
arat
ion
N
S
epar
atio
n o
f si
de-
pro
du
cts
PT
(ML
L),
PS
(LL
)
Page 206
Ap
pen
dic
es
18
6
6
Co
nta
ct p
rob
lem
of
RM
/lim
ited
mas
s tr
ansf
er
Rea
ctio
n
- M
ixin
g
N
Mix
ing
alt
ern
ativ
es
M,
2p
hM
(tw
o p
has
es)
R
eact
ion
-
Mix
ing
N
M
ixin
g a
lter
nat
ives
M
, 2
ph
M,
ES
(D)
7
Exp
losi
ve m
ixtu
re
Rea
ctio
n
Mix
ture
fla
sh p
oin
t R
eact
ion
N
C
oo
lin
g E
S(C
)
Rea
ctio
n
So
lub
ilit
y p
aram
eter
S
epar
atio
n
Y
Mix
ture
fla
sh p
oin
t, r
emo
vin
g o
ne
com
po
un
d a
ffec
ts t
he
flas
h p
oin
t P
C(L
L),
PT
(LL
), P
S(L
L)
Rea
ctio
n
Mo
lar
volu
me,
so
lub
ilit
y p
aram
eter
S
epar
atio
n
N
Mix
ture
fla
sh p
oin
t, r
emo
vin
g o
ne
com
po
un
d a
ffec
ts t
he
flas
h p
oin
t P
T(M
VL
), P
S(V
L)
Rea
ctio
n
Van
der
Waa
ls v
olu
me,
cri
tica
l te
mp
S
epar
atio
n
N
Mix
ture
fla
sh p
oin
t, r
emo
vin
g o
ne
com
po
un
d a
ffec
ts t
he
flas
h p
oin
t P
T(M
VV
), P
S(V
V)
Rea
ctio
n
So
lub
ilit
y p
aram
eter
, ra
diu
s o
f g
yrat
ion
, m
ola
r vo
lum
e S
epar
atio
n
N
Mix
ture
fla
sh p
oin
t, r
emo
vin
g o
ne
com
po
un
d a
ffec
ts t
he
flas
h p
oin
t P
T(M
LL
), P
S(L
L)
8
Deg
rad
atio
n b
y te
mp
erat
ure
R
eact
ion
-
Rea
ctio
n
N
Co
oli
ng
ES
(C)
Rea
ctio
n
So
lub
ilit
y p
aram
eter
S
epar
atio
n
Y
Rem
ovi
ng
pro
du
cts/
des
irab
le s
ide-
pro
du
cts
that
are
deg
rad
ed b
y h
igh
tem
per
atu
res
PC
(LL
), P
T(L
L),
PS
(LL
)
Rea
ctio
n
Mo
lar
volu
me,
so
lub
ilit
y p
aram
eter
S
epar
atio
n
N
Rem
ovi
ng
pro
du
cts/
des
irab
le s
ide-
pro
du
cts
that
are
deg
rad
ed b
y h
igh
tem
per
atu
res
PT
(MV
L),
PS
(VL
)
Rea
ctio
n
Van
der
Waa
ls v
olu
me,
cri
tica
l te
mp
S
epar
atio
n
N
Rem
ovi
ng
pro
du
cts/
des
irab
le s
ide-
pro
du
cts
that
are
deg
rad
ed b
y h
igh
tem
per
atu
res
PT
(MV
V),
PS
(VV
)
Rea
ctio
n
So
lub
ilit
y p
aram
eter
, ra
diu
s o
f g
yrat
ion
, m
ola
r vo
lum
e S
epar
atio
n
N
Rem
ovi
ng
pro
du
cts/
des
irab
le s
ide-
pro
du
cts
that
are
deg
rad
ed b
y h
igh
tem
per
atu
res
PT
(ML
L),
PS
(LL
)
9
Lim
ited
hea
t tr
ansf
er
Rea
ctio
n
- M
ixin
g
N
Incr
ease
hea
t tr
ansf
er
M,
2p
hM
(tw
o p
has
es)
10
Aze
otr
op
e S
epar
atio
n
Vap
or
pre
ssu
re,
solu
bil
ity
par
amet
er
Sep
arat
ion
Y
F
orm
atio
n o
f A
zeo
tro
pe
(s)
2p
hM
, P
C(V
L),
PT
(VL
),
PS
(VL
), E
S(C
), E
S(H
),
PC
(LL
), P
S(L
L)
Sep
arat
ion
K
inet
ic d
iam
eter
, V
an d
er W
aals
vo
lum
e S
epar
atio
n
Y (
S/L
) A
ffin
ity
for
MS
A/F
orm
atio
n o
f A
zeo
tro
pe
PC
(VL
/LS
/VS
),
PS
(VL
/LS
/VS
)
Sep
arat
ion
S
olu
bil
ity
par
amet
er
Sep
arat
ion
Y
F
orm
atio
n o
f A
zeo
tro
pe
(s)
PC
(LL
), P
T(L
L),
PS
(LL
)
Sep
arat
ion
V
apo
r p
ress
ure
, h
eat
of
vap
ori
zati
on
, b
oil
ing
po
int,
so
lub
ilit
y p
aram
eter
S
epar
atio
n
Y
Fo
rmat
ion
of
Aze
otr
op
e (s
) 2
ph
M,
PC
(VL
), P
T(V
L),
P
S(V
L),
ES
(C),
ES
(H)
Sep
arat
ion
V
apo
r p
ress
ure
, h
eat
of
vap
ori
zati
on
, b
oil
ing
po
int
Sep
arat
ion
N
F
orm
atio
n o
f A
zeo
tro
pe
(s)
2p
hM
, P
C(V
L),
PT
(VL
),
PS
(VL
), E
S(C
), E
S(H
)
Sep
arat
ion
M
ola
r vo
lum
e, s
olu
bil
ity
par
amet
er
Sep
arat
ion
N
F
orm
atio
n o
f A
zeo
tro
pe
(s)
PT
(MV
L),
PS
(VL
)
Sep
arat
ion
V
an d
er W
aals
vo
lum
e, c
riti
cal
tem
p
Sep
arat
ion
N
F
orm
atio
n o
f A
zeo
tro
pe
(s)
PT
(MV
V),
PS
(VV
)
Page 207
Ap
pen
dic
es
18
7
Sep
arat
ion
S
olu
bil
ity
par
amet
er
Sep
arat
ion
N
F
orm
atio
n o
f A
zeo
tro
pe
(s)
PT
(ML
L),
PS
(LL
)
11
Deg
rad
atio
n b
y te
mp
erat
ure
S
epar
atio
n
Bo
ilin
g p
oin
t S
epar
atio
n
N
Red
uct
ion
of
tem
per
atu
re
ES
(C)
12
Dif
ficu
lt s
epar
atio
n
du
e to
lo
w d
rivi
ng
fo
rce
Sep
arat
ion
V
apo
r p
ress
ure
, so
lub
ilit
y p
aram
eter
S
epar
atio
n
Y
DF
an
alys
is
2p
hM
, P
C(V
L),
PT
(VL
),
PS
(VL
), E
S(C
), E
S(H
)
S
epar
atio
n
So
lub
ilit
y p
aram
eter
S
epar
atio
n
Y
Aff
init
y fo
r M
SA
P
C(L
L),
PT
(LL
), P
S(L
L)
S
epar
atio
n
Kin
etic
dia
met
er,
Van
der
Waa
ls
volu
me
Sep
arat
ion
Y
(S
/L)
Aff
init
y fo
r M
SA
P
C(V
L/L
S/V
S),
P
S(V
L/L
S/V
S)
S
epar
atio
n
Vap
or
pre
ssu
re,
hea
t o
f va
po
riza
tio
n,
bo
ilin
g p
oin
t, s
olu
bil
ity
par
amet
er
Sep
arat
ion
Y
D
F a
nal
ysis
2
ph
M,
PC
(VL
), P
T(V
L),
P
S(V
L),
ES
(C),
ES
(H)
S
epar
atio
n
Vap
or
pre
ssu
re,
hea
t o
f va
po
riza
tio
n,
bo
ilin
g p
oin
t S
epar
atio
n
N
DF
an
alys
is
2p
hM
, P
C(V
L),
PT
(VL
),
PS
(VL
), E
S(C
), E
S(H
)
S
epar
atio
n
Mo
lar
volu
me,
so
lub
ilit
y p
aram
eter
S
epar
atio
n
N
Co
mp
on
ent
affi
nit
y P
T(M
VL
), P
S(V
L)
S
epar
atio
n
Van
der
Waa
ls v
olu
me,
cri
tica
l te
mp
S
epar
atio
n
N
Co
mp
on
ent
affi
nit
y P
T(M
VV
), P
S(V
V)
S
epar
atio
n
So
lub
ilit
y p
aram
eter
, ra
diu
s o
f g
yrat
ion
, m
ola
r vo
lum
e S
epar
atio
n
N
Co
mp
on
ent
affi
nit
y P
T(M
LL
), P
S(L
L)
13
Hig
h e
ner
gy
con
sum
pti
on
/dem
and
S
epar
atio
n
Vap
or
pre
ssu
re,
solu
bil
ity
par
amet
er
Sep
arat
ion
Y
A
ffin
ity
for
MS
A
PC
(LL
), P
T(L
L),
PS
(LL
)
Sep
arat
ion
K
inet
ic d
iam
eter
, V
an d
er W
aals
vo
lum
e S
epar
atio
n
Y (
S/L
) A
ffin
ity
for
MS
A
PC
(VL
/LS
/VS
),
PS
(VL
/LS
/VS
)
Sep
arat
ion
V
apo
r p
ress
ure
, h
eat
of
vap
ori
zati
on
, b
oil
ing
po
int,
so
lub
ilit
y p
aram
eter
S
epar
atio
n
Y
DF
an
alys
is
2p
hM
, P
C(V
L),
PT
(VL
),
PS
(VL
), E
S(C
), E
S(H
)
Sep
arat
ion
V
apo
r p
ress
ure
, h
eat
of
vap
ori
zati
on
, b
oil
ing
po
int
Sep
arat
ion
N
D
F a
nal
ysis
2
ph
M,
PC
(VL
), P
T(V
L),
P
S(V
L),
ES
(C),
ES
(H))
Sep
arat
ion
M
ola
r vo
lum
e, s
olu
bil
ity
par
amet
er
Sep
arat
ion
N
C
om
po
nen
t af
fin
ity
PT
(MV
L),
PS
(VL
)
Sep
arat
ion
V
an d
er W
aals
vo
lum
e, c
riti
cal
tem
p
Sep
arat
ion
N
C
om
po
nen
t af
fin
ity
PT
(MV
V),
PS
(VV
)
Sep
arat
ion
S
olu
bil
ity
par
amet
er,
rad
ius
of
gyr
atio
n,
mo
lar
volu
me
Sep
arat
ion
N
C
om
po
nen
t af
fin
ity
PT
(ML
L),
PS
(LL
)
14
Insu
ffic
ien
t p
uri
ty
Sep
arat
ion
S
olu
bil
ity
par
amet
er,
mel
tin
g p
oin
t S
epar
atio
n
N
DF
an
alys
is
PT
(LS
), P
S(L
S),
ES
(C/H
)
Sep
arat
ion
M
ola
r vo
lum
e, s
olu
bil
ity
par
amet
er
Sep
arat
ion
N
C
om
po
nen
t af
fin
ity
PT
(MV
L),
PS
(VL
)
S
epar
atio
n
Van
der
Waa
ls v
olu
me,
cri
tica
l te
mp
S
epar
atio
n
N
Co
mp
on
ent
affi
nit
y P
T(M
VV
), P
S(V
V)
S
epar
atio
n
So
lub
ilit
y p
aram
eter
, ra
diu
s o
f g
yrat
ion
, m
ola
r vo
lum
e S
epar
atio
n
N
Co
mp
on
ent
affi
nit
y P
T(M
LL
), P
S(L
L)
Page 208
Ap
pen
dic
es
18
8
C.3
: Id
en
tifi
cati
on
of
pri
nci
ple
PB
Bs
(KB
3.1)
Pro
pe
rty
T
hre
sho
ld
va
lue
s P
oss
ible
Fe
ed
p
ha
se
Pri
nci
ple
SP
B o
r P
BB
s P
oss
ible
ou
tle
t p
ha
se
Ag
en
t a
dd
ed
So
lub
ilit
y p
aram
eter
1.
11
V
PT
(VL
), P
S(V
L)
V
MS
A (
L)
0.0
0
L
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L)
V a
nd
L
MS
A(V
)
Aze
otr
op
e Y
es
V a
nd
/or
L
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L)
V,
L a
nd
LL
M
SA
(L
), E
SA
P
C(L
L),
PS
(LL
)
V a
nd
/or
L
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L),
ES
(C),
ES(
H)
V a
nd
L
MS
A (
L),
ES
A
V a
nd
/or
L
PT
(MV
V),
PS
(VV
) V
E
SA
Rel
ativ
e vo
lati
lity
<
=1.
05
L
PC
(LL
), P
T(L
L),
PS
(LL
) L
M
SA
(L
)
V a
nd
/or
L
PT
(ML
L),
PS
(LL
) L
E
SA
V a
nd
/or
L
PC
(LS
/VS
), P
S(L
S/V
S)
V a
nd
/or
L
MS
A (
S)
V a
nd
/or
L
PT
(MV
L),
PS
(VL
) V
an
d L
E
SA
Aze
otr
op
e an
d
Pre
ssu
re s
ensi
tive
sy
stem
Y
es
V a
nd
/or
L
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L),
ES
(D),
ES
(C),
ES
(H)
V a
nd
L
ES
A
Mel
tin
g p
oin
t 1.
20
L
P
T(L
S),
PS
(LS
), E
S(C
/H)
S a
nd
L a
nd
/or
V
ES
A
Bo
ilin
g p
oin
t,
1.2
3 V
an
d/o
r L
P
T(V
L),
PS(
VL
) V
an
d L
E
SA
V
apo
r p
ress
ure
10
.00
Tri
ple
po
int
tem
per
atu
re
30.0
0
V
PT
(VS
), P
S(V
S)
V a
nd
/or
S
ES
A
Tri
ple
po
int
pre
ssu
re
1.10
Van
der
Waa
ls v
olu
me
1.0
7 V
an
d/o
r L
P
T(M
VV
), P
S(V
V)
V
ES
A
Cri
tica
l te
mp
1.
10
So
lub
ilit
y p
aram
eter
1.
20
V a
nd
/or
L
PT
(ML
L),
PS
(LL
) L
E
SA
R
adiu
s o
f g
yrat
ion
1.
01
Mo
lar
volu
me
1.0
2
Page 209
Ap
pen
dic
es
18
9
Mo
lecu
lar
dia
met
er
2.0
0
Liq
uid
P
C(L
S),
PS
(LS
) L
an
d S
-
Mo
lecu
lar
wei
gh
t 1.
90
Mo
lar
volu
me
1.0
2
V a
nd
/or
L
PT
(MV
L),
PS
(VL
) V
an
d L
E
SA
S
olu
bil
ity
par
amet
er
1.0
0
Tri
ple
po
int
tem
per
atu
re
30.0
0
S
PT
(VS
), P
S(V
S)
V a
nd
/or
S
ES
A
Tri
ple
po
int
pre
ssu
re
1.10
Mo
lecu
lar
dia
met
er
2.0
0
L
PC
(LS
), P
S(L
S)
L a
nd
S
- M
ole
cula
r w
eig
ht
1.7
0
Bo
ilin
g p
oin
t,
1.0
1
Liq
uid
, L
iqu
id
and
Vap
or
2p
hM
, P
C(V
L),
PT
(VL
), P
S(V
L),
ES
(C),
ES(
H)
V a
nd
L
ES
A
Vap
or
pre
ssu
re
1.0
5
Aze
otr
op
e N
o
Van
der
Waa
ls v
olu
me
1.0
7 V
an
d/o
r L
P
C(L
S/V
S),
PS
(LS
/VS
) V
M
SA
(S
)
Kin
etic
dia
met
er
1.0
5
V
PC
(VL
), P
S(V
L)
V a
nd
L
MS
A (
L)
En
do
ther
mic
rea
ctio
n
Hig
h
V a
nd
/or
L
and
/or
S
M,
ES
(D)
V a
nd
/or
L
and
/or
S
ES
A
Page 210
Ap
pen
dic
es
19
0
C.4
: T
ran
sla
tio
n o
f b
asi
c st
ruct
ure
s to
un
it o
pe
rati
on
s (K
B3.
2)
(ex
pa
nd
ed
fro
m L
utz
e,
20
12 a
nd
Ba
bi,
20
14)
SP
B w
ith
in b
asi
c st
ruct
ure
T
ask
R
ea
ctio
n/S
ep
ara
tio
n
un
it-o
pe
rati
on
Scr
ee
nin
g 1
:
Fe
ed
ph
ase
Scr
ee
nin
g 2
: M
SA
-Y/N
S
cre
en
ing
3:
Az
eo
tro
pe
Scr
ee
nin
g 4
:
No
. o
f o
utl
ets
M=
R=
R
eact
ion
R
eact
or
S,
gas
(V
) an
d/o
r L
Y
/N
N
1
=R
=E
S(D
) R
eact
ion
M
icro
wav
e re
acto
r S
, g
as (
V)
and
/or
L
Y/N
N
1
=R
=E
S(D
) R
eact
ion
U
ltra
sou
nd
rea
cto
r S
, g
as (
V)
and
/or
L
Y/N
N
1
=R
=E
S(D
) R
eact
ion
S
on
och
emic
al r
eact
or
S,
gas
(V
) an
d/o
r L
Y
/N
N
1
=P
T(V
L)=
PS
(VL
)/E
S(C
/H)
Sep
arat
ion
P
arti
al c
on
den
sati
on
or
vap
ori
zati
on
V
an
d/o
r L
N
N
1
=P
T(V
L)=
PS
(VL
) S
epar
atio
n
Fla
sh v
apo
riza
tio
n
L
N
N
2
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS(
VL
) S
epar
atio
n
Dis
till
atio
n
V a
nd
/or
L
N
Y/N
2
=P
C(L
L)=
PT
(LL
)=P
S(L
L)
Sep
arat
ion
L
iqu
id–
liq
uid
ext
ract
ion
L
Y
Y
2
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS(
VL
) S
epar
atio
n
Kai
bel
Co
lum
n
V a
nd
/or
L
Y/N
Y
/N
4
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS(
VL
) S
epar
atio
n
Eva
po
rati
on
L
N
N
1
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS(
VL
) S
epar
atio
n
Div
idin
g W
all
Co
lum
n
V a
nd
/or
L
N
N
3
=P
C(L
L)=
PS(
LL
) S
epar
atio
n
Dec
ante
r L
N
Y
/N
2
=P
T(L
S)=
PS
(LS
),P
T(M
LL
/MV
L/M
VV
)=P
S(L
L)/
E
S(H
/C)
Sep
arat
ion
M
emb
ran
e cr
ysta
lliz
atio
n
L
N
N
3
=P
T(M
VV
)=P
S(V
V)
Sep
arat
ion
M
emb
ran
e-V
apo
r-p
erm
eati
on
V
N
Y
2
=P
T(V
L)=
PS
(VL
) S
epar
atio
n
Ab
sorp
tio
n
Gas
or
V
Y
Y/N
2
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS
(VL
), E
S(C
/H)
Sep
arat
ion
E
xtra
ctiv
e d
isti
llat
ion
V
an
d/o
r L
Y
Y
/N
2
=P
C(V
L)=
PS
(VL
) S
epar
atio
n
Ad
sorp
tio
n
V a
nd
/or
L
Y
Y/N
2
=P
C(L
S/V
S)=
PS
(LS
/VS
) S
epar
atio
n
Mo
lecu
lar
siev
e ad
sorp
tio
n
V
Y
Y/N
2
=P
T(M
VL
)=P
S(V
L)
Sep
arat
ion
P
erva
po
rati
on
mem
bra
ne
L
N
Y/N
2
=P
T(M
VV
)=P
S(V
V)
Sep
arat
ion
V
apo
r p
erm
eati
on
m
emb
ran
e V
N
Y
/N
2
Page 211
Ap
pen
dic
es
19
1
=P
T(M
LL
)=P
S(L
L)
Sep
arat
ion
L
iqu
id-l
iqu
id m
emb
ran
e L
N
Y
/N
2
=P
T(L
S)=
PS
(LS
)/E
S(C
/H)
Sep
arat
ion
C
ryst
alli
zati
on
L
Y
/N
N
2
=P
T(V
L)=
PS
(VL
), P
C(L
S),
ES
(H)
Sep
arat
ion
D
ryin
g
L a
nd
S
N
N
2
=P
C(L
L)=
PS(
LL
), E
S(D
) S
epar
atio
n
Cen
trif
ug
al l
iqu
id-l
iqu
id
con
tact
ors
L
an
d/o
r S
N
N
2
=P
T(V
L)=
PS
(VL
), P
C(L
S),
ES
(D)
Sep
arat
ion
M
icro
wav
e d
ryin
g
L a
nd
S
N
N
2
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS(
VL
), E
S(C
/H/D
) S
epar
atio
n
Mic
row
ave
assi
sted
d
isti
llat
ion
V
an
d/o
r L
N
Y
/N
2
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS(
VL
),
=P
T(M
VL
/MV
V/M
LL
)=P
S(L
L,V
V),
ES
(C/H
) S
ep.
+ S
ep.
Mem
bra
ne
dis
till
atio
n
V a
nd
/or
L
N
Y/N
3
=P
C(V
L/V
S/L
S)=
PS
(VL
/VS
/LS
) S
ep.
+ S
ep.
Mu
lti
adso
rpti
on
co
lum
n
V a
nd
or
L
Y
Y/N
3
=2
ph
M=
PC
(VL
)=P
T(V
L)=
PS(
VL
),
=P
C(L
S)=
PS
(LS
), E
S(C
/H)
Sep
. +
Sep
. A
dso
rpti
ve d
isti
llat
ion
V
an
d o
r L
Y
Y
/N
3
=P
T(V
L)=
PS
(VL
),
=P
C(V
L/L
S/V
S)=
PS
(VL
/LS
/VS
) S
ep.
+ S
ep.
Ad
sorp
tive
fla
sh
V a
nd
or
L
Y
Y/N
3
=2
ph
M=
R=
PC
(VL
)=P
T(V
L)=
PS
(VL
) R
eact
ion
+S
epar
atio
n
Rea
ctiv
e D
isti
llat
ion
V
an
d/o
r L
N
Y
/N
2
=2
ph
m=
R=
PC
(LL
)=P
S(L
L)
Rea
ctio
n +
Sep
arat
ion
R
eact
ive
extr
acti
on
co
lum
n
V a
nd
/or
L
N
Y/N
2
=2
ph
M=
R=
PC
(VL
)=P
T(V
L)=
PS
(VL
) R
eact
ion
+S
epar
atio
n
Rea
ctiv
e D
ivid
ing
Wal
l C
olu
mn
V
an
d/o
r L
N
N
3
=R
==
PC
(VL
/VS
/LS
)=P
S(V
L/V
S/L
S)
Rea
ctio
n +
Sep
arat
ion
R
eact
ive
adso
rpti
on
co
lum
n
V a
nd
/or
L
Y
Y/N
2
=R
=P
T(M
LL
)=P
S(L
L)
Rea
ctio
n +
Sep
arat
ion
M
emb
ran
e (l
iqu
id-l
iqu
id)
reac
tor
V a
nd
/or
L
N
Y/N
2
=R
=P
T(M
VV
)=P
S(V
V)
Rea
ctio
n +
Sep
arat
ion
M
emb
ran
e (v
apo
r p
erm
eati
on
) re
acto
r V
an
d/o
r L
N
Y
/N
2
=R
=P
T(M
VL
)=P
S(V
L)
Rea
ctio
n +
Sep
arat
ion
M
emb
ran
e (P
erva
po
rati
on
) re
acto
r V
an
d/o
r L
N
Y
/N
2
=R
=P
C(L
S)=
PS
(LS
) R
eact
ion
+ S
epar
atio
n
Mem
bra
ne
Rea
cto
r (b
io)
L a
nd
/or
S
N
Y/N
2
=2
ph
M=
R=
PC
(VL
)=P
T(V
L)=
PS
(VL
),
=P
T(V
L/L
S/V
S)=
PS
(VL
/LS
/VS
), E
S(C
/H)
Rea
ctio
n +
Sep
. +
Sep
. A
dso
rpti
ve r
eact
ive
dis
till
atio
n
V a
nd
/or
L
Y
Y/N
3
=R
=P
C(V
L)=
PS
(VL
)=P
T(V
L),
PT
(MV
L)
Rea
ctio
n +
Sep
. +
Sep
. M
emb
ran
e re
acti
ve
dis
till
atio
n
V a
nd
/or
L
N
Y/N
3
Page 212
Appendices
192
Appendix D
D.1: Simple mass balance models
o Mixer model: The mass balance model for a mixer consisting of N streams and a single
outlet is as follows:
𝜇𝑖,𝑁𝑀+1= ∑ 𝜇𝑖,𝑗
𝑁𝑚
𝑗=1
Here, μ is the molar flowrate, i denotes the components, j denotes the stream number
while Nm is the number of inlet streams. An example of mixer is shown in Figure D.1.1.
Figure D.1.1: Connections for a mixer
o Reactor model: The mass balance model for a reactor is as follows:
𝜇𝑖,𝑗+1 = 𝜇𝑖,𝑗 + ∑ 𝛾𝑟,𝑖 η𝑟 𝜇𝑖,𝑗
𝑟
Here, 𝛾 is the stoichiometric coefficient, η is the reaction conversion and r denotes the
reactor. An example of reactor is shown in Figure D.1.2.
Figure D.1.2: Connections for a reactor
o Splitter model: The splitter model is generally used to represent the separation unit
operations. This mainly requires the separation factors to calculate the mass balance. The
mass balance equations for a splitter with multiple outlet is as follows:
𝜇𝑖,𝑗+1 = 휀𝑖,𝑗 𝜇𝑖,𝑗
𝜇𝑖,𝑁𝑆 = (1 − ∑ 휀𝑖,𝑗
𝑗
𝑗=1
)𝜇𝑖,𝑗
Here, 휀𝑖,𝑗 denotes the separation factor while NS is the number of streams. An example
of splitter is shown in Figure D.1.3.
µI,j
µI,j+Nm
µI,Nm+1Mixer
µI,j µI,j+1 Reactor
Page 213
Appendices
193
Figure D.1.3: Connections for a splitter
o Divider model: This model can be used for recycle or purge streams where the
composition of all inlet and outlet streams is same. The mass balance equations for the
divider are as follows:
𝜇𝑖,𝑗+1 = 𝛿𝑖,𝑗 𝜇𝑖,𝑗
𝜇𝑖,𝑁𝑆 = (1 − ∑ 𝛿𝑖,𝑗
𝑗
𝑗=1
)𝜇𝑖,𝑗
Here, 𝛿 denotes split fraction. The example of divider is same as splitter in Figure D.1.3.
D.2: Recovery, purity factors and process conditions (adapted from Tula, 2016)
This section of Appendix D provides the values that are used to calculate the mass balance for
generated process alternatives. In case of other unit-operations including intensified options are
calculated based on knowledge based insights.
Unit-operation Recovery Process conditions
Reactor - Reaction conditions
Distillation column
Key component – 0.998, others – 1.00 (above and below key component)
Top – Bubble point (Dew point for non-condensable),
Bottom – bubble point
Crystallizer Key component – 0.999
(purity) Based on melting points
Liquid membrane Key component – 0.995 Same as inlet Vapor permeation membrane
Key component – 0.995 Permeate at bubble point
temperature of key component
Gas membrane Key component – 0.99 Same as inlet
Pervaporation membrane
Key component – 0.99 Permeate at bubble point
temperature of key component
Adsorption Key component – 0.99 Same as inlet/ΔT of 10 OC
Liquid-liquid extraction
Key component – 0.99 Same as inlet
Extractive distillation
Key component – 0.995, others – 1.00 (above and below key component)
Top – Bubble point (Dew point for non-condensable),
Bottom – bubble point
µI,j
µI,1 Splitter
µI,j+NS
Page 214
Appendices
194
Appendix E: Production of DME case study
E.1: Generated feasible flowsheet alternatives
Level 1 Alternative
No. A->BC---ABC A/BC B/C
1 Reactor Adsorption (MSA(S)) Flash
2 Reactor Adsorption (MSA(S)) Vapor permeation membrane
3 Reactor Adsorption (MSA(S)) Distillation
4 Reactor Adsorption (MSA(S)) Adsorption (MSA(S))
A->BC---ABC B/CA C/A
6 Reactor Flash Crystallization
7 Reactor Flash Liquid membrane
8 Reactor Flash Pervaporation membrane
9 Reactor Flash Distillation
10 Reactor Flash Adsorption (MSA(S))
11 Reactor Distillation Crystallization
12 Reactor Distillation Liquid membrane
13 Reactor Distillation Pervaporation membrane
14 Reactor Distillation Distillation
15 Reactor Distillation Adsorption (MSA(S))
16 Reactor Adsorption (MSA(S)) Vapor permeation membrane
17 Reactor Adsorption (MSA(S)) Distillation
18 Reactor Adsorption (MSA(S)) Adsorption (MSA(S))
A->BC---ABC C/AB B/A
19 Reactor Distillation Flash
20 Reactor Distillation Vapor permeation membrane
21 Reactor Distillation Distillation
22 Reactor Distillation Adsorption (MSA(S))
23 Reactor Adsorption (MSA(S)) Flash
24 Reactor Adsorption (MSA(S)) Vapor permeation membrane
25 Reactor Adsorption (MSA(S)) Distillation
26 Reactor Adsorption (MSA(S)) Adsorption (MSA(S))
27 Reactor Flash Flash
28 Reactor Flash Distillation
29 Reactor Flash Adsorption (MSA(S))
Level 2 Alternative
No. A->BC---ABC A/BC---B/C
30 Reactor Membrane (vapor) distillation
Page 215
Appendices
195
31 Reactor Membrane (vapor) adsorption-both
32 Reactor Adsorptive distillation
33 Reactor Multi-stage adsorption
A->BC---ABC B/CA---C/A
34 Reactor Flash crystallization
35 Reactor Flash Membrane (liquid)
36 Reactor Flash distillation
37 Reactor Flash adsorption
38 Reactor Membrane (vapor) distillation
39 Reactor Membrane (vapor) adsorption-both
40 Reactor Distillation Membrane (vapor-liquid)
41 Reactor Distillation Membrane (liquid)
42 Reactor Divided wall column
43 Reactor Adsorptive distillation - both
44 Reactor Multi-stage adsorption
A->BC---ABC C/BA---B/A
45 Reactor Flash membrane (vapor)
46 Reactor Membrane (vapor) distillation-both
47 Reactor Membrane (vapor) adsorption-both
48 Reactor Flash distillation
49 Reactor Adsorptive distillation-both
50 Reactor Divided wall column
51 Reactor Flash adsorption
52 Reactor Multi-stage adsorption
A->BC---ABC----A/BC B/C
53 Membrane (vapor) reactor Flash
54 Membrane (vapor) reactor Vapor permeation membrane
55 Membrane (vapor) reactor Distillation
56 Membrane (vapor) reactor Adsorption (MSA(S))
57 Reactive adsorption Flash
58 Reactive adsorption Vapor permeation membrane
59 Reactive adsorption Distillation
60 Reactive adsorption Adsorption (MSA(S))
A->BC---ABC----B/CA C/A
61 Membrane (vapor) reactor Vapor permeation membrane
62 Membrane (vapor) reactor Distillation
63 Membrane (vapor) reactor Adsorption (MSA(S))
64 Reactive distillation Crystallization
65 Reactive distillation Liquid membrane
Page 216
Appendices
196
66 Reactive distillation Pervaporation membrane
67 Reactive distillation Distillation
68 Reactive distillation Adsorption (MSA(S))
69 Reactive adsorption Vapor permeation membrane
70 Reactive adsorption Distillation
71 Reactive adsorption Adsorption (MSA(S))
A->BC---ABC----C/AB B/A
71 Membrane (vapor) reactor Flash
72 Membrane (vapor) reactor Vapor permeation membrane
73 Membrane (vapor) reactor Distillation
74 Membrane (vapor) reactor Adsorption (MSA(S))
75 Reactive distillation Flash
76 Reactive distillation Distillation
77 Reactive adsorption Flash
78 Reactive adsorption Vapor permeation membrane
79 Reactive adsorption Distillation
80 Reactive adsorption Adsorption (MSA(S))
Level 3
Alternative No.
A->BC---ABC----A/B/C
81 Reactive membrane(vapor) distillation
82 Reactive membrane(vapor) adsorption
83 Reactive adsorptive distillation
84 Reactive multi-stage adsorption
85 Reactive divided wall distillation
A->BC---B/C
86 Membrane reactor (vapor permeation)
87 Reactive distillation
88 Reactive adsorption
E.2: Membrane data for vapor permeation of water (Lee et al., 2004)
Vapor permeation
membrane details
Water flux 0.037 kmol/m2/min
MeOH flux 2.02E-07 kmol/ m2/min
Selectivity (Water : MeOH) 100:1 -
Membrane area Alternative 81 142.38 m2
Alternative 74 142.51 m2
E.3: Adsorption data for adsorption of MeOH (Rao et al., 2007) – Alternative 74
Adsorbent
capacity (w/w) 14.03
Adsorbent
required 1798.81 kg/12 hr
Page 217
Appendices
197
Appendix F: Hydrodealkylation (HDA) of toluene case study
F.1: Overview of analysis for existing process flowsheet (base case) (Tula, 2016)
Figure F.1.1: Utility cost for HDA base case flowsheet
Figure F.1.2: Carbon footprint for HDA base case flowsheet
Table F.1.1: Sustainability analysis for HDA base case flowsheet
Path Component Flow-rate (kg/h) MVA (103$/yr) EWC (103$/yr) TVA(103$/yr)
OP 2 H2 283.23 -3258.98 34.04 -3293.03
OP 7 Methane 2005.51 -9843.81 8.88 -9852.69
CP 9 Toluene 4094.35 - 662.76 -
15
,3
0,0
13
,8
2,0
0,3
68
,5
UTI
LITY
CO
ST %
EQUIPMENT UNIT OPERATION
T1-RB T1-CD T2-RB T2-CD CRZ HEXC
O2
EQU
IVA
LEN
T
EQUIPMENT UNIT OPERATION
HEX T1-RB T1-CD T2-RB T2-CD CRZ
Page 218
Appendices
198
OP 2 – H2 Feed -> HEX -> REC -> HEX -> FLSH -> PUR ->
OP 7 – CH4 Feed -> HEX -> REC -> HEX -> FLSH -> PUR ->
CP 9 – T1 -> T2 -> REC -> CRY -> HEX -> REC -> HEX-> FLS -> T1
Here, OP is open path, while CP is close path. H2: Hydrogen, CH4: Methane, HEX: Heat
exchanger, REC: reactor, FLSH: Flash, PUR: Purge, T1: Distillation column 1, T2: Distillation
column 2, CRY: Crystallizer
Table F.1.2: LCA indicators for HDA base case flowsheet
Indicator Impact factor
HTPI 51.05
HTPE 47.48
ATP 59.20
GWP 7.90
Page 219
Appendices
199
F.2: Level 2 phenomena based superstructure of alternatives
A + C B + D
2D A + E
--ABCDE--
M=2phM=R(V)=ES(C) V
AB/CDE---C/ED
M=P T(MVV)=PS(V V)
M=PC(VS/LS)=PS(VS/LS)*
AB/CDE---CD/E
M=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PT(VL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(MVV)=PS(VV)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(VS/LS)=PS(VS/LS)*
M=PC(VS/LS)=P S(VS/LS)**
M=PT(MVL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
AB/CDE---D/EC
M=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(MVL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PC(VS/LS)=PS(VS/LS)**
M=PT(VL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PT(MVV)=PS(VV)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=PC(VL)=PT(V L)=P S(VL
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
AB/CDE---C/DE
M=P T(VL)=PS(VL)
M=PT(MV L)=P S(VL)
M=P T(VL)=PS(VL)
M=PC(VS/LS)=P S(VS/LS)*
M=PT(MVV)=P S(VV)
M=PC(VS/VL)=PS(VS/VL)*
M=2phM=ES(C)=PC(VL)=PT(V L)=P S(VL)
M=2phM=PC(VL)=PT(V L)=P S(VL)
M=2phM=ES(H)=PC(VL)=PT(V L)=P S(VL)
M=PT(MVL)=P S(VL)
M=2phM=ES(C)=PC(VL)=PT(V L)=P S(VL)
M=2phM=PC(VL)=PT(V L)=P S(VL)
M=PC(VS/LS)=P S(VS/LS)*
M=2phM=PC(VL)=PT(VL)=PS(V L
M=2phM=ES(H)=PC(VL)=PT(V L)=P S(VL)
M=PT(MVL)=PS(VL)
M=PC(VS/LS)=P S(VS/LS)*
M=PC(VS/LS)=PS(V S/LS)**
D/E
M=PT(VL)=PS(VL)
M=P T(MVV)=PS(VV)
M=PC(LS)=PS(LS)
M=PT(MVL)=PS(V L)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(V L)
M=2phM=PC(VL)=PT(VL)=PS(V L)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(V L)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)
M=ES(C)
C/D
M=PT(LS)=P S(LS)
M=ES(C)
M=PT(MVL)=PS(V L)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(V L)
M=2phM=PC(VL)=PT(VL)=PS(V L)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(V L)
M=PC(VS/LS)=PS(VS/LS)*
M=PC(LL)=PT(LL)PS(LL)*
M=2phM=E S(C)=P C(VL)=PT(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)*
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
C/E
M=PT(VL)=PS(VL)
M=P T(MVV)=PS(VV)
M=PT(MV L)=P S(VL)
M=2phM=ES(C)=PC(VL)=PT(V L)=P S(VL)
M=2phM=PC(VL)=PT(V L)=P S(VL)
M=2phM=ES(H)=PC(VL)=PT(V L)=P S(VL)
M=PC(VS/LS)=P S(VS/LS)*
M=PT(LS)=PS(LS)
M=ES(C)
Reaction taskSeparation-
Separation taskSeparation task
Level 2a
V-L
V-L
V-V
V-L
V-L
V-L
V-L
V-V
V-L
V-L
V-V
V-L
V-L
V-L
V-L
V-L
V-V
V-L
V-L
V-L
V-L
V-L
V-V
V-V
V-L
V-L
V-V
V-L
V-L
Page 220
Appendices
200
C/DE
C/ED
D/E
C/D
M=PT(MVV)=PS(VV)
M=PT(MVL)=PS(VL)
M=PC(VL/V S/LS)=PS(VL/VS/LS)*
M=P T(LS)=PS(LS)
M=ES(C/H)
M=PT(MV L)=P S(VL)
M=2phM=ES(C)=PC(VL)=PT(V L)=P S(VL)
M=2phM=PC(VL)=PT(V L)=P S(VL)
M=2phM=ES(H)=PC(VL)=PT(V L)=P S(VL)
M=PC(V L/VS/LS)=P S(VL/VS/LS)*
D/EC
M=PT(VL)=PS(VL)
M=PT(MVV)=P S(VV)
M=PC(LS)=PS(LS)
M=PT(MVL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
CD/E
M=PT(VL)=P S(VL)
M=P T(MVV)=PS(V V)
M=PC(LS)=PS(LS)
M=PT(MV L)=P S(VL)
M=2phM=ES(C)=PC(VL)=PT(V L)=P S(VL)
M=2phM=PC(VL)=PT(V L)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=P S(VS/LS)*
M=PT(LS)=P S(LS)
M=ES(C)
M=P T(VL)=PS(VL)
M=PT(MVV)=P S(VV)
M=PC(LS)=PS(LS)
M=PT(MVL)=PS(VL)
M=2phM=E S(C)=P C(V L)=P T(VL)=PS(VL)
M=2phM=P C(V L)=P T(VL)=PS(VL)
M=2phM=E S(H)=P C(V L)=P T(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=P T(LS)=PS(LS)
M=ES(C/H)
C/E
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PT(MVL)=PS(V L)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(V L)
M=2phM=PC(VL)=PT(VL)=PS(V L)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(V L)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)
M=E S(C)
M=PC(LL)=PT(LL)PS(LL)*
M=2phM=E S(C)=P C(V L)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)*
M=2phM=E S(H)=P C(V L)=PT(VL)=PS(VL)
D/CE
M=PC(LL)=PT(LL)PS(LL)*
M=2phM=ES(C)=PC(VL)=PT(VL)=P S(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)*
M=2phM=ES(H)=PC(VL)=PT(VL)=P S(VL)
M=PC(LL)=PT(LL)PS(LL)*
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(V L)
M=2phM=PC(VL)=PT(VL)=PS(VL)*
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(V L)
M=PT(LS)=PS(LS)
M=E S(C)
V-V
A + C B + D
2D A + E
--ABCDE—AB/CDE
M=2phM=R(V)=E S(C)
M=P T(MVV)=PS(VV)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(V L)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=ES(C)
M=PC(VS/LS)=P S(VS/LS)*
M=PC(VL/VS/LS)=PS(V L/VS/LS)*
Reaction-Separation
taskSeparation task Separation task
Level 2b
V-L
V-V
L-S
V-L
V-L/V-V
L-L
V-L
V-V
L-S
V-L
V-V
L-S
V-L
V-L
V-L/V-V
L-L
V-L
V-L/V-V
V-L
V-V
L-S
V-L
V-L
Page 221
Appendices
201
A + C B + D
2D A + E
--ABCDE--
M=2phM=R(V)=ES(C)
AB/CDE
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS)=PS(VS)*
V
M=PT(LS)=PS(LS)
M=ES(C)
M=PT(MV L)=PS(V L)
M=PT(LS)=PS(LS)
M=ES(C)
M=PC(VS/LS)=PS(V S/LS)*
M=PT(VL)=PS(VL)
M=PT(MV L)=PS(V L)
M=PT(VL)=PS(VL)
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(V S/LS)*
D/EC---C/E
M=PT(MVL)=PS(VL)
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MV L)=PS(V L)
M=PC(VS/LS)=PS(V S/LS)*
M=2phM=ES(C)=P C(V L)=P T(V L)=P S(V L)
M=2phM=PC(VL)=P T(VL)=P S(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=P T(VL)=P S(VL)
M=2phM=ES(H)=P C(V L)=P T(V L)=P S(V L)
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVV)=PS(V V)
M=PT(MVV)=PS(V V)
M=PC(VS/LS)=PS(V S/LS)*
M=PT(LS)=PS(LS)
M=ES(C)
M=P T(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
CD/E---C/D
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(V S/LS)*
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=ES(C)=P C(V L)=PT(V L)=PS(V L)
M=2phM=PC(VL)=P T(VL)=P S(VL)
M=2phM=ES(H)=P C(V L)=PT(V L)=PS(V L)
M=P T(MVV)=PS(VV)
M=P T(MVV)=PS(VV)
M=PC(V S/LS)=PS(VS/LS)*
C/DE---D/E
M=P T(LS)=P S(LS)
M=ES(C)
M=P T(MVL)=PS(VL
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=P T(LS)=P S(LS)
M=ES(C)
M=PC(VS/LS)=PS(VS/LS)*
M=PC(LS)=P S(LS)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PC(LS)=P S(LS)
M=PT(MVL)=PS(VL)
C/ED---D/E
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PT(MVV)=PS(VV)
M=PC(VS/LS)=PS(V S/LS)*
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(V S/LS)*
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(V S/LS)*
Reaction taskSeparation-
Separation task
Level 2c
Separation-
Separation task
Separation-
Separation task
V-L
V-V
V-L
V-V
Page 222
Appendices
202
F.3: Level 3 phenomena-based superstructure of alternatives
C/E
M=PT(VL)=PS(VL)
M=P T(MVV)=PS(VV)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)
M=ES(C)
A + C B + D
2D A + E
--ABCDE---AB/CDE---C/DE
M=PT(MVV)=PS(VV)
M=2phM=R(V)=ES(C)
M=PC(VS/LS)=PS(VS/LS)*
M=P T(MVV)=PS(VV)
M=2phM=ES(C)=PC(V L)=P T(V L)=P S(V L)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(V L)=P T(V L)=P S(V L)
M=2phM=ES(C)=PC(V L)=P T(V L)=P S(V L)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(V L)=P T(V L)=P S(V L)
M=PC(VS/LS)=PS(VS/LS)*
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=R(V)=ES(C)
M=PC(V S/LS)=PS(VS/LS)*
D/E
M=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(LS)=P S(LS)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(LS)=PS(LS)
M=ES(C)
A + C B + D
2D A + E
--ABCDE---AB/CDE---C/ED
M=PT(MVV)=PS(VV)
M=2phM=R(V)=ES(C)
M=PC(V S/LS)=P S(VS/LS)*
A + C B + D
2D A + E
--ABCDE---AB/CDE---CD/E
M=PT(MVV)=PS(VV)
M=2phM=R(V)=ES(C)
M=PC(V S/LS)=P S(VS/LS)*
M=PT(MV V)=P S(VV)
M=2phM=ES(C)=P C(V L)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=P C(V L)=PT(VL)=PS(VL)
M=2phM=ES(C)=P C(V L)=PT(VL)=PS(VL)
M=2phM=PC(V L)=P T(V L)=P S(V L)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(V L)=P T(V L)=P S(V L)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=P C(V L)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=P C(V L)=PT(VL)=PS(VL)
M=PT(MVL)=P S(VL)
M=2phM=ES(C)=P C(V L)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(V S/LS)=P S(VS/LS)*
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=R(V)=ES(C)
M=PT(MVL)=P S(VL)
M=PC(V S/LS)=P S(VS/LS)*
M=2phM=R(V)=ES(C)
M=PC(V S/LS)=P S(VS/LS)*
C/D
M=PT(LS)=PS(LS)
M=ES(C)
M=P T(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL/VS/LS)=PS(VL/V S/LS)*
M=PC(LL)=PT(LL)PS(LL)*
M=2phM=ES(C)=P C(V L)=PT(V L)=PS(V L)
M=2phM=P C(V L)=PT(V L)=PS(V L)*
M=2phM=ES(H)=P C(V L)=PT(V L)=PS(V L)
A + C B + D
2D A + E
--ABCDE---AB/CDE---D/EC
M=PT(MVV)=PS(VV)
M=2phM=R(V)=E S(C)
M=PC(VS/LS)=PS(VS/LS)*
M=PT(MVV)=PS(VV)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=P C(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=P C(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=R(V)=P C(VL)=PT(VL)=PS(VL)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=R(V)=ES(C)
M=PC(VS/LS)=PS(VS/LS)*
A + C B + D
2D A + E
--ABCDE--
M=2phM=R(V)=ES(C)
AB/CDE---CD/E---C/D
M=PT(MVV)=PS(VV)
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=R(V)=ES(C)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
M=2phM=E S(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=PC(VL)=PT(VL)=PS(VL)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=E S(H)=PC(VL)=PT(VL)=PS(VL)
AB/CDE---CD/E---C/D
M=PC(V S/LS)=PS(VS/LS)*
M=2phM=R(V)=ES(C)
M=PC(VS/LS)=PS(VS/LS)*
M=P T(MVL)=PS(VL)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=P T(V L)=P S(V L)
M=PC(V S/LS)=PS(VS/LS)*
M=2phM=PC(VL)=P T(V L)=P S(V L)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=2phM=ES(C)=P C(V L)=PT(V L)=PS(V L)
M=PC(VS/LS)=PS(VS/LS)*
M=2phM=PC(VL)=P T(V L)=P S(V L)
M=PC(V S/LS)=PS(VS/LS)*
M=2phM=ES(H)=P C(V L)=PT(V L)=PS(V L)
M=P T(MVV)=PS(VV)
M=2phM=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=2phM=PC(VL)=P T(V L)=P S(V L)
M=PC(V S/LS)=PS(VS/LS)*
M=2phM=PC(VL)=P T(V L)=P S(V L)
M=2phM=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MVV)=PS(VV)
M=PC(V S/LS)=PS(VS/LS)*
M=2phM=R(V)=ES(C)
M=PC(V S/LS)=PS(VS/LS)*
Reaction-Separation-
Separation taskSeparation task
Level 3
Separation-Separation-Separation task
Reaction task
Page 223
Appendices
203
F.4: Generated feasible flowsheet alternatives
Level 1
ABCDE (A+C--B+D, 2D--A+E) AB/CDE C/DE D/E
1 Reaction Flash distillation Crystallization Melting 2 Reaction Flash distillation Pervaporation membrane Crystallization 3 Reaction Flash distillation Pervaporation membrane Flash 4 Reaction Flash distillation Pervaporation membrane Pervaporation membrane 5 Reaction Flash distillation Pervaporation membrane Distillation 6 Reaction Flash distillation Pervaporation membrane Adsorption (solid MSA) 7 Reaction Flash distillation Adsorption (solid/liquid MSA) Crystallization 8 Reaction Flash distillation Adsorption (solid/liquid MSA) Flash 9 Reaction Flash distillation Adsorption (solid/liquid MSA) Pervaporation membrane 10 Reaction Flash distillation Adsorption (solid/liquid MSA) Distillation 11 Reaction Flash distillation Adsorption (solid/liquid MSA) Adsorption (solid MSA) 12 Reaction Distillation Crystallization Melting 13 Reaction Distillation Pervaporation membrane Crystallization 14 Reaction Distillation Pervaporation membrane Flash 15 Reaction Distillation Pervaporation membrane Pervaporation membrane 16 Reaction Distillation Pervaporation membrane Distillation 17 Reaction Distillation Pervaporation membrane Adsorption (solid MSA) 18 Reaction Distillation Adsorption (solid/liquid MSA) Crystallization 19 Reaction Distillation Adsorption (solid/liquid MSA) Flash 20 Reaction Distillation Adsorption (solid/liquid MSA) Pervaporation membrane 21 Reaction Distillation Adsorption (solid/liquid MSA) Distillation 22 Reaction Distillation Adsorption (solid/liquid MSA) Adsorption (solid MSA) 23 Reaction Adsorption (solid MSA) Crystallization Melting 24 Reaction Adsorption (solid MSA) Pervaporation membrane Crystallization 25 Reaction Adsorption (solid MSA) Pervaporation membrane Flash 26 Reaction Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 27 Reaction Adsorption (solid MSA) Pervaporation membrane Distillation 28 Reaction Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 29 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Crystallization 30 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Flash 31 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Pervaporation membrane 32 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Distillation 33 Reaction Adsorption (solid MSA) Adsorption (solid/liquid MSA) Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E)
AB/CDE C/ED D/E
34 Reaction Adsorption (solid MSA) Vapor permeation membrane Flash 35 Reaction Adsorption (solid MSA) Vapor permeation membrane Vapor permeation membrane 36 Reaction Adsorption (solid MSA) Vapor permeation membrane Distillation 37 Reaction Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E) AB/CDE CD/E C/D
38 Reaction Flash distillation Crystallization Crystallization 39 Reaction Flash distillation Crystallization Pervaporation membrane 40 Reaction Flash distillation Crystallization Distillation 41 Reaction Flash distillation Crystallization Adsorption (solid/liquid MSA) 42 Reaction Flash distillation Flash distillation Crystallization 43 Reaction Flash distillation Flash distillation Pervaporation membrane 44 Reaction Flash distillation Flash distillation Distillation 45 Reaction Flash distillation Flash distillation Adsorption (solid/liquid MSA) 46 Reaction Flash distillation Pervaporation membrane Crystallization 47 Reaction Flash distillation Pervaporation membrane Pervaporation membrane
Page 224
Appendices
204
48 Reaction Flash distillation Pervaporation membrane Distillation 49 Reaction Flash distillation Pervaporation membrane Adsorption (solid/liquid MSA) 50 Reaction Flash distillation Distillation Crystallization 51 Reaction Flash distillation Distillation Pervaporation membrane 52 Reaction Flash distillation Distillation Distillation 53 Reaction Flash distillation Distillation Adsorption (solid/liquid MSA) 54 Reaction Flash distillation Adsorption (solid MSA) Crystallization 55 Reaction Flash distillation Adsorption (solid MSA) Pervaporation membrane 56 Reaction Flash distillation Adsorption (solid MSA) Distillation 57 Reaction Flash distillation Adsorption (solid MSA) Adsorption (solid/liquid MSA) 58 Reaction Distillation Crystallization Crystallization 59 Reaction Distillation Crystallization Pervaporation membrane 60 Reaction Distillation Crystallization Distillation 61 Reaction Distillation Crystallization Adsorption (solid MSA) 62 Reaction Distillation Flash distillation Crystallization 63 Reaction Distillation Flash distillation Pervaporation membrane 64 Reaction Distillation Flash distillation Distillation 65 Reaction Distillation Flash distillation Adsorption (solid MSA) 66 Reaction Distillation Pervaporation membrane Crystallization 67 Reaction Distillation Pervaporation membrane Pervaporation membrane 68 Reaction Distillation Pervaporation membrane Distillation 69 Reaction Distillation Pervaporation membrane Adsorption (solid MSA) 70 Reaction Distillation Distillation Crystallization 71 Reaction Distillation Distillation Pervaporation membrane 72 Reaction Distillation Distillation Distillation 73 Reaction Distillation Distillation Adsorption (solid MSA) 74 Reaction Distillation Adsorption (solid MSA) Crystallization 75 Reaction Distillation Adsorption (solid MSA) Pervaporation membrane 76 Reaction Distillation Adsorption (solid MSA) Distillation 77 Reaction Distillation Adsorption (solid MSA) Adsorption (solid MSA) 78 Reaction Adsorption (solid MSA) Crystallization Crystallization 79 Reaction Adsorption (solid MSA) Crystallization Pervaporation membrane 80 Reaction Adsorption (solid MSA) Crystallization Distillation 81 Reaction Adsorption (solid MSA) Crystallization Adsorption (solid MSA) 82 Reaction Adsorption (solid MSA) Flash distillation Crystallization 83 Reaction Adsorption (solid MSA) Flash distillation Pervaporation membrane 84 Reaction Adsorption (solid MSA) Flash distillation Distillation 85 Reaction Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 86 Reaction Adsorption (solid MSA) Vapor permeation membrane Distillation 87 Reaction Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 88 Reaction Adsorption (solid MSA) Pervaporation membrane Crystallization 89 Reaction Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 90 Reaction Adsorption (solid MSA) Pervaporation membrane Distillation 91 Reaction Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 92 Reaction Adsorption (solid MSA) Distillation Crystallization 93 Reaction Adsorption (solid MSA) Distillation Pervaporation membrane 94 Reaction Adsorption (solid MSA) Distillation Distillation 95 Reaction Adsorption (solid MSA) Distillation Adsorption (solid MSA) 96 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Crystallization 97 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Pervaporation membrane 98 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Distillation 99 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E)
AB/CDE D/EC C/E
100 Reaction Flash distillation Flash distillation Crystallization
101 Reaction Flash distillation Flash distillation Flash distillation
Page 225
Appendices
205
102 Reaction Flash distillation Flash distillation Pervaporation membrane 103 Reaction Flash distillation Flash distillation Distillation 104 Reaction Flash distillation Flash distillation Adsorption (solid MSA) 105 Reaction Flash distillation Crystallization Crystallization 106 Reaction Flash distillation Crystallization Flash distillation 107 Reaction Flash distillation Crystallization Pervaporation membrane 108 Reaction Flash distillation Crystallization Distillation 109 Reaction Flash distillation Crystallization Adsorption (solid MSA) 110 Reaction Flash distillation Pervaporation membrane Crystallization 111 Reaction Flash distillation Pervaporation membrane Flash distillation 112 Reaction Flash distillation Pervaporation membrane Pervaporation membrane 113 Reaction Flash distillation Pervaporation membrane Distillation 114 Reaction Flash distillation Pervaporation membrane Adsorption (solid MSA) 115 Reaction Flash distillation Distillation Crystallization 116 Reaction Flash distillation Distillation Flash distillation 117 Reaction Flash distillation Distillation Pervaporation membrane 118 Reaction Flash distillation Distillation Distillation 119 Reaction Flash distillation Distillation Adsorption (solid MSA) 120 Reaction Flash distillation Adsorption (solid MSA) Crystallization 121 Reaction Flash distillation Adsorption (solid MSA) Flash distillation 122 Reaction Flash distillation Adsorption (solid MSA) Pervaporation membrane 123 Reaction Flash distillation Adsorption (solid MSA) Distillation 124 Reaction Flash distillation Adsorption (solid MSA) Adsorption (solid MSA) 125 Reaction Distillation Flash distillation Crystallization 126 Reaction Distillation Flash distillation Flash distillation 127 Reaction Distillation Flash distillation Pervaporation membrane 128 Reaction Distillation Flash distillation Distillation 129 Reaction Distillation Flash distillation Adsorption (solid MSA) 130 Reaction Distillation Crystallization Crystallization 131 Reaction Distillation Crystallization Flash distillation 132 Reaction Distillation Crystallization Pervaporation membrane 133 Reaction Distillation Crystallization Distillation 134 Reaction Distillation Crystallization Adsorption (solid MSA) 135 Reaction Distillation Pervaporation membrane Crystallization 136 Reaction Distillation Pervaporation membrane Flash distillation 137 Reaction Distillation Pervaporation membrane Pervaporation membrane 138 Reaction Distillation Pervaporation membrane Distillation 139 Reaction Distillation Pervaporation membrane Adsorption (solid MSA) 140 Reaction Distillation Distillation Crystallization 141 Reaction Distillation Distillation Flash distillation 142 Reaction Distillation Distillation Pervaporation membrane 143 Reaction Distillation Distillation Distillation 144 Reaction Distillation Distillation Adsorption (solid MSA) 145 Reaction Distillation Adsorption (solid MSA) Crystallization 146 Reaction Distillation Adsorption (solid MSA) Flash distillation 147 Reaction Distillation Adsorption (solid MSA) Pervaporation membrane 148 Reaction Distillation Adsorption (solid MSA) Distillation 149 Reaction Distillation Adsorption (solid MSA) Adsorption (solid MSA) 150 Reaction Adsorption (solid MSA) Flash distillation Crystallization 151 Reaction Adsorption (solid MSA) Flash distillation Flash distillation 152 Reaction Adsorption (solid MSA) Flash distillation Pervaporation membrane 153 Reaction Adsorption (solid MSA) Flash distillation Distillation 154 Reaction Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 155 Reaction Adsorption (solid MSA) Vapor permeation membrane Flash distillation 156 Reaction Adsorption (solid MSA) Vapor permeation membrane Vapor permeation membrane 157 Reaction Adsorption (solid MSA) Vapor permeation membrane Distillation
Page 226
Appendices
206
158 Reaction Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 159 Reaction Adsorption (solid MSA) Pervaporation membrane Flash distillation 160 Reaction Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 161 Reaction Adsorption (solid MSA) Pervaporation membrane Distillation 162 Reaction Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 163 Reaction Adsorption (solid MSA) Distillation Crystallization 164 Reaction Adsorption (solid MSA) Distillation Flash distillation 165 Reaction Adsorption (solid MSA) Distillation Pervaporation membrane 166 Reaction Adsorption (solid MSA) Distillation Distillation 167 Reaction Adsorption (solid MSA) Distillation Adsorption (solid MSA) 168 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Flash distillation 169 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Distillation 170 Reaction Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)
Level 2a
ABCDE (A+C--B+D, 2D--A+E)
AB/CDE C/DE---D/E
171 Reaction Flash distillation Membrane (pervaporation) crystallization 172 Reaction Flash distillation Membrane distillation (pervaporation) 173 Reaction Flash distillation Membrane adsorption (pervaporation) 174 Reaction Flash distillation Adsorption (solid MSA) crystallization 175 Reaction Flash distillation Membrane adsorption (pervaporation) 176 Reaction Flash distillation Adsorptive (solid MSA) distillation 177 Reaction Flash distillation Multi stage adsorption 178 Reaction Vapor permeation membrane Membrane crystallization (pervaporation) 179 Reaction Vapor permeation membrane Membrane distillation (pervaporation) 180 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 181 Reaction Vapor permeation membrane Adsorption (solid MSA) crystallization 182 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 183 Reaction Vapor permeation membrane Adsorptive (solid MSA) distillation 184 Reaction Vapor permeation membrane Multi stage adsorption 185 Reaction Distillation Membrane crystallization (pervaporation) 186 Reaction Distillation Membrane distillation (pervaporation) 187 Reaction Distillation Membrane adsorption (pervaporation) 188 Reaction Distillation Adsorption (solid MSA) crystallization 189 Reaction Distillation Membrane adsorption (pervaporation) 190 Reaction Distillation Adsorptive (solid MSA) distillation 191 Reaction Distillation Multi stage adsorption 192 Reaction Adsorption (solid MSA) Membrane crystallization (pervaporation) 193 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 194 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 195 Reaction Adsorption (solid MSA) Adsorption (solid MSA) crystallization 196 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 197 Reaction Adsorption (solid MSA) Adsorptive (solid MSA) distillation 198 Reaction Adsorption (solid MSA) Multi stage adsorption
ABCDE (A+C--B+D, 2D--A+E) AB/CDE C/ED---D/E
199 Reaction Vapor permeation membrane Membrane distillation (vapor permeation) 200 Reaction Vapor permeation membrane Membrane adsorption (vapor permeation) 201 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 202 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation)
203 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 204 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation)
ABCDE (A+C--B+D, 2D--A+E)
AB/CDE CD/E---C/D
Page 227
Appendices
207
205 Reaction Flash distillation Membrane crystallization (pervaporation) 206 Reaction Flash distillation Membrane crystallization (pervaporation) 207 Reaction Flash distillation Adsorption (solid MSA) crystallization 208 Reaction Flash distillation Membrane flash 209 Reaction Flash distillation Flash distillation 210 Reaction Flash distillation Adsorptive flash 211 Reaction Flash distillation Membrane crystallization (pervaporation) 212 Reaction Flash distillation Membrane distillation (pervaporation) 213 Reaction Flash distillation Membrane adsorption (pervaporation) 214 Reaction Flash distillation Membrane distillation (pervaporation) 215 Reaction Flash distillation Divided wall distillation 216 Reaction Flash distillation Adsorptive distillation 217 Reaction Flash distillation Adsorption (solid MSA) crystallization 218 Reaction Flash distillation Membrane adsorption (pervaporation) 219 Reaction Flash distillation Adsorptive distillation 220 Reaction Flash distillation Multi stage adsorption 221 Reaction Vapor permeation membrane Membrane flash (vapor permeation) 222 Reaction Vapor permeation membrane Flash distillation 223 Reaction Vapor permeation membrane Adsorptive flash 224 Reaction Vapor permeation membrane Membrane distillation (vapor permeation) 225 Reaction Vapor permeation membrane Membrane adsorption (vapor permeation) 226 Reaction Vapor permeation membrane Membrane distillation (pervaporation) 227 Reaction Vapor permeation membrane Divided wall distillation 228 Reaction Vapor permeation membrane Adsorptive distillation 229 Reaction Vapor permeation membrane Adsorption (solid MSA) crystallization 230 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 231 Reaction Vapor permeation membrane Adsorptive distillation 232 Reaction Vapor permeation membrane Multi stage adsorption 233 Reaction Distillation Membrane crystallization (pervaporation) 234 Reaction Distillation Adsorption (solid MSA) crystallization 235 Reaction Distillation Membrane flash (pervaporation) 236 Reaction Distillation Flash distillation 237 Reaction Distillation Adsorptive flash 238 Reaction Distillation Membrane crystallization (pervaporation) 239 Reaction Distillation Membrane distillation (pervaporation) 240 Reaction Distillation Membrane adsorption (pervaporation) 241 Reaction Distillation Membrane distillation (pervaporation) 242 Reaction Distillation Divided wall distillation 243 Reaction Distillation Adsorptive distillation 244 Reaction Distillation Adsorption (solid MSA) crystallization 245 Reaction Distillation Membrane adsorption (pervaporation) 246 Reaction Distillation Adsorptive distillation 247 Reaction Distillation Multi stage adsorption 248 Reaction Adsorption (solid MSA) Membrane flash 249 Reaction Adsorption (solid MSA) Flash distillation 250 Reaction Adsorption (solid MSA) Adsorptive flash 251 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 252 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation) 253 Reaction Adsorption (solid MSA) Membrane crystallization (pervaporation) 254 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 255 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 256 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 257 Reaction Adsorption (solid MSA) Divided wall distillation 258 Reaction Adsorption (solid MSA) Adsorptive distillation 259 Reaction Adsorption (solid MSA) Adsorption (solid MSA) crystallization 260 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation)
Page 228
Appendices
208
261 Reaction Adsorption (solid MSA) Adsorptive distillation 262 Reaction Adsorption (solid MSA) Multi stage adsorption
ABCDE (A+C--B+D, 2D--A+E) AB/CDE D/EC---C/E
263 Reaction Flash distillation Membrane flash (pervaporation) 264 Reaction Flash distillation Flash distillation 265 Reaction Flash distillation Adsorptive flash 266 Reaction Flash distillation Membrane crystallization (pervaporation) 267 Reaction Flash distillation Adsorption (solid MSA) crystallization 268 Reaction Flash distillation Membrane crystallization (pervaporation) 269 Reaction Flash distillation Membrane distillation (pervaporation) 270 Reaction Flash distillation Membrane adsorption (pervaporation) 271 Reaction Flash distillation Membrane distillation (pervaporation) 272 Reaction Flash distillation Divided wall column 273 Reaction Flash distillation Adsorptive distillation 274 Reaction Flash distillation Membrane adsorption (pervaporation) 275 Reaction Flash distillation Adsorptive distillation 276 Reaction Flash distillation Multi stage adsorption 277 Reaction Vapor permeation membrane Membrane flash (pervaporation) 278 Reaction Vapor permeation membrane Flash distillation 279 Reaction Vapor permeation membrane Adsorptive flash 280 Reaction Vapor permeation membrane Membrane distillation (vapor permeation) 281 Reaction Vapor permeation membrane Membrane adsorption (vapor permeation) 282 Reaction Vapor permeation membrane Membrane distillation (pervaporation) 283 Reaction Vapor permeation membrane Divided wall column 284 Reaction Vapor permeation membrane Adsorptive distillation 285 Reaction Vapor permeation membrane Membrane adsorption (pervaporation) 286 Reaction Vapor permeation membrane Adsorptive distillation 287 Reaction Vapor permeation membrane Multi stage adsorption 288 Reaction Distillation Membrane flash (pervaporation) 289 Reaction Distillation Flash distillation 290 Reaction Distillation Adsorptive flash 291 Reaction Distillation Membrane crystallization (pervaporation) 292 Reaction Distillation Adsorption (solid MSA) crystallization 293 Reaction Distillation Membrane crystallization (pervaporation) 294 Reaction Distillation Membrane distillation (pervaporation) 295 Reaction Distillation Membrane adsorption (pervaporation) 296 Reaction Distillation Membrane distillation (pervaporation) 297 Reaction Distillation Divided wall column 298 Reaction Distillation Adsorptive distillation 299 Reaction Distillation Membrane adsorption (pervaporation) 300 Reaction Distillation Adsorptive distillation 301 Reaction Distillation Multi stage adsorption 302 Reaction Adsorption (solid MSA) Membrane flash (pervaporation) 303 Reaction Adsorption (solid MSA) Flash distillation 304 Reaction Adsorption (solid MSA) Adsorptive flash 305 Reaction Adsorption (solid MSA) Membrane distillation (vapor permeation) 306 Reaction Adsorption (solid MSA) Membrane adsorption (vapor permeation) 307 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 308 Reaction Adsorption (solid MSA) Membrane adsorption (pervaporation) 309 Reaction Adsorption (solid MSA) Membrane distillation (pervaporation) 310 Reaction Adsorption (solid MSA) Divided wall column 311 Reaction Adsorption (solid MSA) Adsorptive distillation 312 Reaction Adsorption (solid MSA) Adsorptive distillation 313 Reaction Adsorption (solid MSA) Multi stage adsorption
Page 229
Appendices
209
Level 2b
ABCDE (A+C--B+D, 2D--A+E)
AB/CDE---C/DE D/E
314 Reaction Membrane (pervaporation) flash Crystallization 315 Reaction Membrane (pervaporation) flash Flash 316 Reaction Membrane (pervaporation) flash Pervaporation membrane 317 Reaction Membrane (pervaporation) flash Distillation 318 Reaction Membrane (pervaporation) flash Adsorption (solid MSA) 319 Reaction Adsorptive (solid MSA) flash Crystallization 320 Reaction Adsorptive (solid MSA) flash Flash 321 Reaction Adsorptive (solid MSA) flash Pervaporation membrane 322 Reaction Adsorptive (solid MSA) flash Distillation 323 Reaction Adsorptive (solid MSA) flash Adsorption (solid MSA) 324 Reaction Membrane adsorption (vapor permeation) Crystallization 325 Reaction Membrane adsorption (vapor permeation) Flash 326 Reaction Membrane adsorption (vapor permeation) Pervaporation membrane 327 Reaction Membrane adsorption (vapor permeation) Distillation 328 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 329 Reaction Membrane distillation (pervaporation) Crystallization 330 Reaction Membrane distillation (pervaporation) Flash 331 Reaction Membrane distillation (pervaporation) Pervaporation membrane 332 Reaction Membrane distillation (pervaporation) Distillation 333 Reaction Membrane distillation (pervaporation) Adsorption (solid MSA) 334 Reaction Adsorptive (solid MSA) distillation Crystallization 335 Reaction Adsorptive (solid MSA) distillation Flash 336 Reaction Adsorptive (solid MSA) distillation Pervaporation membrane 337 Reaction Adsorptive (solid MSA) distillation Distillation 338 Reaction Adsorptive (solid MSA) distillation Adsorption (solid MSA) 339 Reaction Membrane adsorption (pervaporation) Crystallization 340 Reaction Membrane adsorption (pervaporation) Flash 341 Reaction Membrane adsorption (pervaporation) Pervaporation membrane 342 Reaction Membrane adsorption (pervaporation) Distillation 343 Reaction Membrane adsorption (pervaporation) Adsorption (solid MSA) 344 Reaction Multi stage adsorption Crystallization 345 Reaction Multi stage adsorption Flash 346 Reaction Multi stage adsorption Pervaporation membrane 347 Reaction Multi stage adsorption Distillation 348 Reaction Multi stage adsorption Adsorption (solid MSA) 349 Reaction Membrane adsorption (vapor permeation) Flash 350 Reaction Membrane adsorption (vapor permeation) Vapor permeation membrane 351 Reaction Membrane adsorption (vapor permeation) Distillation 352 Reaction Membrane adsorption (vapor permeation) Adsorption (solid/liquid MSA)
ABCDE (A+C--B+D, 2D--A+E) AB/CDE---CD/E C/D
353 Reaction Membrane flash (pervaporation) Crystallization 354 Reaction Membrane flash (pervaporation) Pervaporation membrane 355 Reaction Membrane flash (pervaporation) Distillation 356 Reaction Membrane flash (pervaporation) Adsorption (solid MSA) 357 Reaction Flash distillation Crystallization 358 Reaction Flash distillation Pervaporation membrane 359 Reaction Flash distillation Distillation 360 Reaction Flash distillation Adsorption (solid MSA) 361 Reaction Adsorptive flash Crystallization 362 Reaction Adsorptive flash Pervaporation membrane 363 Reaction Adsorptive flash Distillation 364 Reaction Adsorptive flash Adsorption (solid MSA)
Page 230
Appendices
210
365 Reaction Membrane flash (vapor permeation) Crystallization 366 Reaction Membrane flash (vapor permeation) Pervaporation membrane 367 Reaction Membrane flash (vapor permeation) Distillation 368 Reaction Membrane flash (vapor permeation) Adsorption (solid MSA) 369 Reaction Membrane distillation (vapor permeation) Crystallization 370 Reaction Membrane distillation (vapor permeation) Pervaporation membrane 371 Reaction Membrane distillation (vapor permeation) Distillation 372 Reaction Membrane distillation (vapor permeation) Adsorption (solid MSA) 373 Reaction Membrane adsorption (vapor permeation) Crystallization 374 Reaction Membrane adsorption (vapor permeation) Pervaporation membrane 375 Reaction Membrane adsorption (vapor permeation) Distillation 376 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 377 Reaction Flash distillation Crystallization 378 Reaction Flash distillation Pervaporation membrane 379 Reaction Flash distillation Distillation 380 Reaction Flash distillation Adsorption (solid MSA) 381 Reaction Membrane distillation (pervaporation) Crystallization 382 Reaction Membrane distillation (pervaporation) Pervaporation membrane 383 Reaction Membrane distillation (pervaporation) Distillation 384 Reaction Membrane distillation (pervaporation) Adsorption (solid MSA) 385 Reaction Divided wall distillation Crystallization 386 Reaction Divided wall distillation Pervaporation membrane 387 Reaction Divided wall distillation Distillation 388 Reaction Divided wall distillation Adsorption (solid MSA) 389 Reaction Adsorptive distillation Crystallization 390 Reaction Adsorptive distillation Pervaporation membrane 391 Reaction Adsorptive distillation Distillation 392 Reaction Adsorptive distillation Adsorption (solid MSA) 393 Reaction Adsorptive flash Crystallization 394 Reaction Adsorptive flash Pervaporation membrane 395 Reaction Adsorptive flash Distillation 396 Reaction Adsorptive flash Adsorption (solid MSA) 397 Reaction Membrane adsorption (vapor permeation) Distillation 398 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 399 Reaction Membrane adsorption (pervaporation) Crystallization 400 Reaction Membrane adsorption (pervaporation) Pervaporation membrane 401 Reaction Membrane adsorption (pervaporation) Distillation 402 Reaction Membrane adsorption (pervaporation) Adsorption (solid MSA) 403 Reaction Adsorptive distillation Crystallization 404 Reaction Adsorptive distillation Pervaporation membrane 405 Reaction Adsorptive distillation Distillation 406 Reaction Adsorptive distillation Adsorption (solid MSA) 407 Reaction Multi stage adsorption Crystallization 408 Reaction Multi stage adsorption Pervaporation membrane 409 Reaction Multi stage adsorption Distillation 410 Reaction Multi stage adsorption Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E) AB/CDE---D/EC C/E
411 Reaction Membrane flash (pervaporation) Crystallization 412 Reaction Membrane flash (pervaporation) Flash distillation 413 Reaction Membrane flash (pervaporation) Pervaporation membrane 414 Reaction Membrane flash (pervaporation) Distillation 415 Reaction Membrane flash (pervaporation) Adsorption (solid MSA) 416 Reaction Flash distillation Crystallization 417 Reaction Flash distillation Flash distillation 418 Reaction Flash distillation Pervaporation membrane
Page 231
Appendices
211
419 Reaction Flash distillation Distillation 420 Reaction Flash distillation Adsorption (solid MSA) 421 Reaction Adsorptive flash Crystallization 422 Reaction Adsorptive flash Flash distillation 423 Reaction Adsorptive flash Pervaporation membrane 424 Reaction Adsorptive flash Distillation 425 Reaction Adsorptive flash Adsorption (solid MSA) 426 Reaction Membrane flash (vapor permeation) Crystallization 427 Reaction Membrane flash (vapor permeation) Flash distillation 428 Reaction Membrane flash (vapor permeation) Pervaporation membrane 429 Reaction Membrane flash (vapor permeation) Distillation 430 Reaction Membrane flash (vapor permeation) Adsorption (solid MSA) 431 Reaction Membrane distillation (vapor permeation) Crystallization 432 Reaction Membrane distillation (vapor permeation) Flash distillation 433 Reaction Membrane distillation (vapor permeation) Pervaporation membrane 434 Reaction Membrane distillation (vapor permeation) Distillation 435 Reaction Membrane distillation (vapor permeation) Adsorption (solid MSA) 436 Reaction Membrane adsorption (vapor permeation) Crystallization 437 Reaction Membrane adsorption (vapor permeation) Flash distillation 438 Reaction Membrane adsorption (vapor permeation) Pervaporation membrane 439 Reaction Membrane adsorption (vapor permeation) Distillation 440 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 441 Reaction Flash distillation Crystallization 442 Reaction Flash distillation Flash distillation 443 Reaction Flash distillation Pervaporation membrane 444 Reaction Flash distillation Distillation 445 Reaction Flash distillation Adsorption (solid MSA) 446 Reaction Membrane distillation (pervaporation) Crystallization 447 Reaction Membrane distillation (pervaporation) Flash distillation 448 Reaction Membrane distillation (pervaporation) Pervaporation membrane 449 Reaction Membrane distillation (pervaporation) Distillation 450 Reaction Membrane distillation (pervaporation) Adsorption (solid MSA) 451 Reaction Divided wall column Crystallization 452 Reaction Divided wall column Flash distillation 453 Reaction Divided wall column Pervaporation membrane 454 Reaction Divided wall column Distillation 455 Reaction Divided wall column Adsorption (solid MSA) 456 Reaction Adsorptive distillation Crystallization 457 Reaction Adsorptive distillation Flash distillation 458 Reaction Adsorptive distillation Pervaporation membrane 459 Reaction Adsorptive distillation Distillation 460 Reaction Adsorptive distillation Adsorption (solid MSA) 461 Reaction Adsorptive flash Crystallization 462 Reaction Adsorptive flash Flash distillation 463 Reaction Adsorptive flash Pervaporation membrane 464 Reaction Adsorptive flash Distillation 465 Reaction Adsorptive flash Adsorption (solid MSA) 466 Reaction Membrane adsorption (vapor permeation) Flash distillation 467 Reaction Membrane adsorption (vapor permeation) Vapor permeation membrane 468 Reaction Membrane adsorption (vapor permeation) Distillation 469 Reaction Membrane adsorption (vapor permeation) Adsorption (solid MSA) 470 Reaction Membrane adsorption (pervaporation) Flash distillation 471 Reaction Membrane adsorption (pervaporation) Pervaporation membrane 472 Reaction Membrane adsorption (pervaporation) Distillation 473 Reaction Membrane adsorption (pervaporation) Adsorption (solid MSA) 474 Reaction Adsorptive distillation Crystallization
Page 232
Appendices
212
475 Reaction Adsorptive distillation Flash distillation 476 Reaction Adsorptive distillation Pervaporation membrane 477 Reaction Adsorptive distillation Distillation 478 Reaction Adsorptive distillation Adsorption (solid MSA) 479 Reaction Multi stage adsorption Flash distillation 480 Reaction Multi stage adsorption Distillation 481 Reaction Multi stage adsorption Adsorption (solid MSA)
Level 2c
ABCDE (A+C--B+D, 2D--A+E)---AB/CDE C/DE D/E
482 Membrane reactor (vapor permeation) Crystallization Melting 483 Membrane reactor (vapor permeation) Pervaporation membrane Crystallization 484 Membrane reactor (vapor permeation) Pervaporation membrane Flash 485 Membrane reactor (vapor permeation) Pervaporation membrane Pervaporation membrane 486 Membrane reactor (vapor permeation) Pervaporation membrane Distillation 487 Membrane reactor (vapor permeation) Pervaporation membrane Adsorption (solid MSA) 488 Membrane reactor (vapor permeation) Adsorption (solid MSA) Crystallization 489 Membrane reactor (vapor permeation) Adsorption (solid MSA) Flash 490 Membrane reactor (vapor permeation) Adsorption (solid MSA) Pervaporation membrane 491 Membrane reactor (vapor permeation) Adsorption (solid MSA) Distillation 492 Membrane reactor (vapor permeation) Adsorption (solid MSA) Adsorption (solid MSA) 493 Reactive distillation Crystallization Melting 494 Reactive distillation Pervaporation membrane Crystallization 495 Reactive distillation Pervaporation membrane Flash 496 Reactive distillation Pervaporation membrane Pervaporation membrane 497 Reactive distillation Pervaporation membrane Distillation 498 Reactive distillation Pervaporation membrane Adsorption (solid MSA) 499 Reactive distillation Adsorption (solid MSA) Crystallization 500 Reactive distillation Adsorption (solid MSA) Flash 501 Reactive distillation Adsorption (solid MSA) Pervaporation membrane 502 Reactive distillation Adsorption (solid MSA) Distillation 503 Reactive distillation Adsorption (solid MSA) Adsorption (solid MSA) 504 Reactive adsorption Crystallization Melting 505 Reactive adsorption Pervaporation membrane Crystallization 506 Reactive adsorption Pervaporation membrane Flash 507 Reactive adsorption Pervaporation membrane Pervaporation membrane 508 Reactive adsorption Pervaporation membrane Distillation 509 Reactive adsorption Pervaporation membrane Adsorption (solid MSA) 510 Reactive adsorption Adsorption (solid MSA) Crystallization 511 Reactive adsorption Adsorption (solid MSA) Flash 512 Reactive adsorption Adsorption (solid MSA) Pervaporation membrane 513 Reactive adsorption Adsorption (solid MSA) Distillation 514 Reactive adsorption Adsorption (solid MSA) Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E)---AB/CDE C/ED D/E
515 Membrane reactor (vapor permeation) Vapor permeation membrane Flash 516 Membrane reactor (vapor permeation) Vapor permeation membrane Distillation 517 Membrane reactor (vapor permeation) Vapor permeation membrane Adsorption (solid MSA) 518 Reactive adsorption Vapor permeation membrane Flash
519 Reactive adsorption Vapor permeation membrane Vapor permeation membrane 520 Reactive adsorption Vapor permeation membrane Distillation 521 Reactive adsorption Vapor permeation membrane Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E)---AB/CDE CD/E C/D
Page 233
Appendices
213
522 Membrane reactor (vapor permeation) Distillation Crystallization 523 Membrane reactor (vapor permeation) Distillation Pervaporation membrane 524 Membrane reactor (vapor permeation) Distillation Distillation 525 Membrane reactor (vapor permeation) Distillation Adsorption (solid MSA) 526 Membrane reactor (vapor permeation) Adsorption (solid MSA) Crystallization 527 Membrane reactor (vapor permeation) Adsorption (solid MSA) Pervaporation membrane 528 Membrane reactor (vapor permeation) Adsorption (solid MSA) Distillation 529 Membrane reactor (vapor permeation) Adsorption (solid MSA) Adsorption (solid MSA) 530 Reactive distillation Crystallization Crystallization 531 Reactive distillation Crystallization Pervaporation membrane 532 Reactive distillation Crystallization Distillation 533 Reactive distillation Crystallization Adsorption (solid MSA) 534 Reactive distillation Flash distillation Crystallization 535 Reactive distillation Flash distillation Pervaporation membrane 536 Reactive distillation Flash distillation Distillation 537 Reactive distillation Flash distillation Adsorption (solid MSA) 538 Reactive distillation Pervaporation membrane Crystallization 539 Reactive distillation Pervaporation membrane Pervaporation membrane 540 Reactive distillation Pervaporation membrane Distillation 541 Reactive distillation Pervaporation membrane Adsorption (solid MSA) 542 Reactive distillation Distillation Crystallization 543 Reactive distillation Distillation Pervaporation membrane 544 Reactive distillation Distillation Distillation 545 Reactive distillation Distillation Adsorption (solid MSA) 546 Reactive distillation Adsorption (solid MSA) Crystallization 547 Reactive distillation Adsorption (solid MSA) Pervaporation membrane 548 Reactive distillation Adsorption (solid MSA) Distillation 549 Reactive distillation Adsorption (solid MSA) Adsorption (solid MSA) 550 Reactive Adsorption (solid MSA) Crystallization Crystallization 551 Reactive Adsorption (solid MSA) Crystallization Pervaporation membrane 552 Reactive Adsorption (solid MSA) Crystallization Distillation 553 Reactive Adsorption (solid MSA) Crystallization Adsorption (solid MSA) 554 Reactive Adsorption (solid MSA) Flash distillation Crystallization 555 Reactive Adsorption (solid MSA) Flash distillation Pervaporation membrane 556 Reactive Adsorption (solid MSA) Flash distillation Distillation 557 Reactive Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 558 Reactive Adsorption (solid MSA) Vapor permeation membrane Distillation 559 Reactive Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 560 Reactive Adsorption (solid MSA) Pervaporation membrane Crystallization 561 Reactive Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 562 Reactive Adsorption (solid MSA) Pervaporation membrane Distillation 563 Reactive Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 564 Reactive Adsorption (solid MSA) Distillation Crystallization 565 Reactive Adsorption (solid MSA) Distillation Pervaporation membrane 566 Reactive Adsorption (solid MSA) Distillation Distillation 567 Reactive Adsorption (solid MSA) Distillation Adsorption (solid MSA) 568 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Crystallization 569 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Pervaporation membrane 570 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Distillation 571 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E)---AB/CDE D/EC C/E
572 Membrane reactor (vapor permeation) Flash distillation Crystallization 573 Membrane reactor (vapor permeation) Flash distillation Flash distillation 574 Membrane reactor (vapor permeation) Flash distillation Pervaporation membrane 575 Membrane reactor (vapor permeation) Flash distillation Distillation
Page 234
Appendices
214
576 Membrane reactor (vapor permeation) Flash distillation Adsorption (solid MSA) 577 Membrane reactor (vapor permeation) Vapor permeation membrane Crystallization 578 Membrane reactor (vapor permeation) Vapor permeation membrane Flash distillation 579 Membrane reactor (vapor permeation) Vapor permeation membrane Vapor permeation membrane 580 Membrane reactor (vapor permeation) Vapor permeation membrane Pervaporation membrane 581 Membrane reactor (vapor permeation) Vapor permeation membrane Distillation 582 Membrane reactor (vapor permeation) Vapor permeation membrane Adsorption (solid MSA) 583 Membrane reactor (vapor permeation) Distillation Crystallization 584 Membrane reactor (vapor permeation) Distillation Flash distillation 585 Membrane reactor (vapor permeation) Distillation Pervaporation membrane 586 Membrane reactor (vapor permeation) Distillation Distillation 587 Membrane reactor (vapor permeation) Distillation Adsorption (solid MSA) 588 Membrane reactor (vapor permeation) Adsorption (solid MSA) Crystallization 589 Membrane reactor (vapor permeation) Adsorption (solid MSA) Flash distillation 590 Membrane reactor (vapor permeation) Adsorption (solid MSA) Pervaporation membrane 591 Membrane reactor (vapor permeation) Adsorption (solid MSA) Distillation 592 Membrane reactor (vapor permeation) Adsorption (solid MSA) Adsorption (solid MSA) 593 Reactive distillation Flash distillation Crystallization 594 Reactive distillation Flash distillation Flash distillation 595 Reactive distillation Flash distillation Pervaporation membrane 596 Reactive distillation Flash distillation Distillation 597 Reactive distillation Flash distillation Adsorption (solid MSA) 598 Reactive distillation Crystallization Crystallization 599 Reactive distillation Crystallization Flash distillation 600 Reactive distillation Crystallization Pervaporation membrane 601 Reactive distillation Crystallization Distillation 602 Reactive distillation Crystallization Adsorption (solid MSA) 603 Reactive distillation Pervaporation membrane Crystallization 604 Reactive distillation Pervaporation membrane Flash distillation 605 Reactive distillation Pervaporation membrane Pervaporation membrane 606 Reactive distillation Pervaporation membrane Distillation 607 Reactive distillation Pervaporation membrane Adsorption (solid MSA) 608 Reactive distillation Distillation Crystallization 609 Reactive distillation Distillation Flash distillation 610 Reactive distillation Distillation Pervaporation membrane 611 Reactive distillation Distillation Distillation 612 Reactive distillation Distillation Adsorption (solid MSA) 613 Reactive distillation Adsorption (solid MSA) Crystallization 614 Reactive distillation Adsorption (solid MSA) Flash distillation 615 Reactive distillation Adsorption (solid MSA) Pervaporation membrane 616 Reactive distillation Adsorption (solid MSA) Distillation 617 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA) 618 Reactive Adsorption (solid MSA) Flash distillation Crystallization 619 Reactive Adsorption (solid MSA) Flash distillation Flash distillation 620 Reactive Adsorption (solid MSA) Flash distillation Pervaporation membrane 621 Reactive Adsorption (solid MSA) Flash distillation Distillation 622 Reactive Adsorption (solid MSA) Flash distillation Adsorption (solid MSA) 623 Reactive Adsorption (solid MSA) Vapor permeation membrane Flash distillation 624 Reactive Adsorption (solid MSA) Vapor permeation membrane Vapor permeation membrane 625 Reactive Adsorption (solid MSA) Vapor permeation membrane Distillation 626 Reactive Adsorption (solid MSA) Vapor permeation membrane Adsorption (solid MSA) 627 Reactive Adsorption (solid MSA) Pervaporation membrane Flash distillation 628 Reactive Adsorption (solid MSA) Pervaporation membrane Pervaporation membrane 629 Reactive Adsorption (solid MSA) Pervaporation membrane Distillation 630 Reactive Adsorption (solid MSA) Pervaporation membrane Adsorption (solid MSA) 631 Reactive Adsorption (solid MSA) Distillation Crystallization
Page 235
Appendices
215
632 Reactive Adsorption (solid MSA) Distillation Flash distillation 633 Reactive Adsorption (solid MSA) Distillation Pervaporation membrane 634 Reactive Adsorption (solid MSA) Distillation Distillation 635 Reactive Adsorption (solid MSA) Distillation Adsorption (solid MSA) 636 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Flash distillation 637 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Distillation 638 Reactive Adsorption (solid MSA) Adsorption (solid MSA) Adsorption (solid MSA)
Level 3a ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---C/DE D/E
639 Reactive Membrane adsorption (vapor permeation) Flash 640 Reactive Membrane adsorption (vapor permeation) Vapor permeation membrane 641 Reactive Membrane adsorption (vapor permeation) Distillation 642 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA) 643 Reactive Membrane distillation (pervaporation) Crystallization 644 Reactive Membrane distillation (pervaporation) Flash 645 Reactive Membrane distillation (pervaporation) Pervaporation membrane 646 Reactive Membrane distillation (pervaporation) Distillation 647 Reactive Membrane distillation (pervaporation) Adsorption (solid MSA) 648 Reactive Adsorptive (solid MSA) distillation Crystallization 649 Reactive Adsorptive (solid MSA) distillation Flash 650 Reactive Adsorptive (solid MSA) distillation Pervaporation membrane 651 Reactive Adsorptive (solid MSA) distillation Distillation 652 Reactive Adsorptive (solid MSA) distillation Adsorption (solid MSA) 653 Reactive Membrane adsorption (pervaporation) Crystallization 654 Reactive Membrane adsorption (pervaporation) Flash 655 Reactive Membrane adsorption (pervaporation) Pervaporation membrane 656 Reactive Membrane adsorption (pervaporation) Distillation 657 Reactive Membrane adsorption (pervaporation) Adsorption (solid MSA) 658 Reactive Multi stage adsorption Vapor permeation membrane 659 Reactive Multi stage adsorption Flash 660 Reactive Multi stage adsorption Distillation 661 Reactive Multi stage adsorption Adsorption (solid MSA) ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---C/ED D/E
662 Reactive Membrane adsorption (vapor permeation) Flash 663 Reactive Membrane adsorption (vapor permeation) Vapor permeation membrane 664 Reactive Membrane adsorption (vapor permeation) Distillation
665 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---CD/E C/D
666 Reactive Membrane distillation (vapor permeation) Pervaporation membrane 667 Reactive Membrane distillation (vapor permeation) Distillation 668 Reactive Membrane distillation (vapor permeation) Adsorption (solid MSA) 669 Reactive Membrane distillation (pervaporation) Crystallization 670 Reactive Membrane distillation (pervaporation) Pervaporation membrane 671 Reactive Membrane distillation (pervaporation) Distillation 672 Reactive Membrane distillation (pervaporation) Adsorption (solid MSA) 673 Reactive divided wall column Crystallization 674 Reactive divided wall column Pervaporation membrane 675 Reactive divided wall column Distillation 676 Reactive divided wall column Adsorption (solid MSA) 677 Reactive Adsorptive (solid MSA) distillation Crystallization 678 Reactive Adsorptive (solid MSA) distillation Pervaporation membrane 679 Reactive Adsorptive (solid MSA) distillation Distillation
Page 236
Appendices
216
680 Reactive Adsorptive (solid MSA) distillation Adsorption (solid MSA) 681 Reactive Membrane adsorption (vapor permeation) Distillation 682 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA) 683 Reactive Membrane adsorption (pervaporation) Crystallization 684 Reactive Membrane adsorption (pervaporation) Pervaporation membrane 685 Reactive Membrane adsorption (pervaporation) Distillation 686 Reactive Membrane adsorption (pervaporation) Adsorption (solid MSA) 687 Reactive Multi stage adsorption Distillation 688 Reactive Multi stage adsorption Adsorption (solid MSA)
ABCDE (A+C--B+D, 2D--A+E)---AB/CDE---D/EC E/C
689 Reactive Membrane distillation (vapor permeation) Flash 690 Reactive Membrane distillation (vapor permeation) Vapor permeation membrane 691 Reactive Membrane distillation (vapor permeation) Distillation 692 Reactive Membrane distillation (vapor permeation) Adsorption (solid MSA) 693 Reactive Membrane distillation (pervaporation) Crystallization 694 Reactive Membrane distillation (pervaporation) Flash 695 Reactive Membrane distillation (pervaporation) Pervaporation membrane 696 Reactive Membrane distillation (pervaporation) Distillation 697 Reactive Membrane distillation (pervaporation) Adsorption (solid MSA) 698 Reactive Membrane adsorption (vapor permeation) Flash 699 Reactive Membrane adsorption (vapor permeation) Vapor permeation membrane 700 Reactive Membrane adsorption (vapor permeation) Distillation 701 Reactive Membrane adsorption (vapor permeation) Adsorption (solid MSA) 702 Reactive divided wall column Crystallization 703 Reactive divided wall column Flash 704 Reactive divided wall column Pervaporation membrane 705 Reactive divided wall column Distillation 706 Reactive divided wall column Adsorption (solid MSA) 707 Reactive Adsorptive (solid MSA) distillation Crystallization 708 Reactive Adsorptive (solid MSA) distillation Flash 709 Reactive Adsorptive (solid MSA) distillation Pervaporation membrane 710 Reactive Adsorptive (solid MSA) distillation Distillation 711 Reactive Adsorptive (solid MSA) distillation Adsorption (solid MSA) 712 Reactive Multi stage adsorption Crystallization 713 Reactive Multi stage adsorption Flash 714 Reactive Multi stage adsorption Pervaporation membrane 715 Reactive Multi stage adsorption Distillation 716 Reactive Multi stage adsorption Adsorption (solid MSA)
Level 3b
ABCDE (A+C--B+D, 2D--A+E)
AB/CDE---CD/E---C/D
717 Reaction Adsorptive membrane (vapor permeation) distillation 718 Reaction Multi stage membrane adsorption (vapor permeation) 719 Reaction Adsorptive membrane distillation (pervaporation) 720 Reaction Divided wall adsorptive distillation 721 Reaction Multi stage adsorptive distillation
ABCDE (A+C--B+D, 2D--A+E)
AB/CDE---D/EC---C/E
722 Reaction Adsorptive membrane distillation (Pervaporation) 723 Reaction Multi stage adsorptive membrane (Pervaporation) 724 Reaction Multi stage adsorptive distillation 725 Reaction Adsorptive membrane distillation (vapor permeation) 726 Reaction Multi stage adsorptive membrane (vapor permeation)
Page 237
Appendices
217
A/B
Membrane (gas permeation) Adsorption (MSA(S))
AB/CDE---A/B
Flash membrane (gas permeation) Membrane (gas permeation) distillation Membrane (gas permeation adsorption) Multi stage adsorption Adsorptive distillation Adsorptive flash
F.5: Membrane data for permeation of hydrogen (Konda et al., (2006) and Fischer
and Iribarren, (2011))
Gas membrane
details
Hydrogen flux 0.201 kmol/m2/h
Methane flux 1.83E-03 kmol/ m2/h
Selectivity (Hydrogen: Methane) 110:1 -
Membrane area Alternative 118 771.97 m2
Alternative 272 784.03 m2
Page 238
Appendices
218
Appendix G: Production of bio-succinic acid case study
G.1: Price of raw material (RM), product and utilities
Table G.1.1: Price of the raw material and product $/kg (Synthesis stage)
Compound Price
(Scenario 1 and 2)
Price
(Scenario 3)
Glucose (GLU) 0.428 0.270
Glycerol (GLY) 0.925 0.230
Sucrose (SUC) 0.485 0.265
Maltose (MAL) 0.485 0.265
Succinic acid (SUCA) 2.860 2.860
Table G.1.2: Price of the utilities (Synthesis stage)
Utility Price
(Scenario 1 and 2)
Price
(Scenario 3)
LP Steam ($/t) 27.000 5.000
Cooling water ($/m3) 0.057 0.490
Electricity ($/kWh) 0.120 0.080
G.2: VLE diagram for water-acetic acid and water-ethanol (using PRO/IITM)
Figure G.2.1: VLE diagram for water-acetic acid (Pirola et al., 2014)
Page 239
Appendices
219
Figure G.2.2: VLE diagram for water-ethanol
Page 240
Appendices
220
G.3: Level 2 and 3 phenomena based superstructure of alternatives
F/EG
D/EG
D/GE
--E/G—(or FE/G or DE/G)--
E/GD/EFG
D/FGE
DEFG/I
L
Separation task - 2 Separation task - 3 Separation task - 4 Separation task - 5
Fermentation--DEFGI/J
Reaction task-
Separation task - 1
DF/GE
M=2phM=R(L)
M=PC(LS)=PS(LS)
M=PC(LS)=PS(LS)* M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
D/GEF
M=PC(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
F/EGD
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PS(VL)
M=PC(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
DFE/G
M=PC(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PC(TS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PC(LS)=PS(LS)*
M=PC(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PC(LS)=PS(LS)*
M=PC(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PC(LS)=PS(LS)*
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
S*/G
V-L
V-L
L-L
Level 2a
L-L
V-L
L-S
V-L
V-L
V-L
L-L
V-L
V-L
L-L
V-L
L-S
V-L
V-L
L-L
V-L
V-L
L-S
L-S
L-L
V-L
V-L
V-L
V-L
L-S
L-S
L-L
L-L
V-L
V-L
V-L
V-L
L-L
L-L
L-S
Page 241
Appendices
221
E/GD/FGE--F/EG
L
Separation task – 2 and 3 Separation task - 4
Fermentation
--DEFGIJ--
Reaction task
DEFGI/J
Separation task - 1
DF/GE—E/G
L-SM=2phM=R(L) M=PC(LS)=PS(LS) M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
F/EGD--D/EG
M=PC(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PC(LS)=PS(LS)*
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
S*/G
V-L
V-L
L-L
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PC(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MLL)=PS(LL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MVL)=PS(VL)
M=PC(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PC(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(VL)=PS(VL)
M=ES(C/H)
M=PT(LS)=PS(LS)
M=PC(VL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MLL)=PS(LL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MVL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(LS)=PS(LS)*
M=PT(MLL)=PS(LL)
M=PC(LS)=PS(LS)*
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(C/H)
M=PT(LS)=PS(LS)
V-L
V-L
V-L
V-L
V-L
V-L
L-S
V-L-S
V-L
V-L
V-L-S
V-L
V-L
V-L
L-S
V-L-S
V-L
L-L
V-L
V-L
L-S
Level 2b
Page 242
Appendices
222
F/EG-E/G
D/EG—E/G
E/GD/EFG
D/FGE
L-S
Separation task - 2 Separation task – 3 and 4 Separation task
Fermentation
--DEFGJ--
Reaction task
DEFG/J
Separation task - 1
DF/GE
L-S LM=2phM=R(L) M=PC(LS)=PS(LS) M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
D/GEF
M=PC(VL)=PS(VL)
F/EGD
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PC(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
DFE/G
M=PC(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PT(MVL)=PS(VL)
M=PC(TS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PC(LS)=PS(LS)*
M=PT(LS)=PS(LS)
M=ES(C/H)
--(DF/D/F)E/G--S*/G
L-L
L-L
L-L
L-L
L-S
V-L
L-S
V-L
V-L
V-L
V-L
V-L
V-L
V-L
V-L
L-S
L-L
V-L
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MLL)=PS(LL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MVL)=PS(VL)
M=PC(LS)=PS(LS)*
M=PT(MLL)=PS(LL)
M=PC(LS)=PS(LS)*
M=PT(MVL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MLL)=PS(LL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MVL)=PS(VL)
M=PC(LS)=PS(LS)*
M=PT(MLL)=PS(LL)
M=PC(LS)=PS(LS)*
M=PT(MVL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MLL)=PS(LL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=PT(MVL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(C/H)
M=PT(LS)=PS(LS)
M=PC(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PC(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(VL)=PS(VL)
M=ES(C/H)
M=PT(LS)=PS(LS)
M=PC(VL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
D/GE—G/E
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=PT(MLL)=PS(LL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PT(MLL)=PS(LL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)*=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=PT(MVL)=PS(VL)
M=PC(LL)=PT(LL)=PS(LL)*
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
E/G
M=PT(LS)=PS(LS)
M=ES(C/H)
Level 2c
V-L
Page 243
Appendices
223
E/GD/FGE--F/EG-E/G
Separation-Separation-
separationSeparation task
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PT(LS)=PS(LS)
M=ES(C/H)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PC(VL)=PT(VL)=PS(VL)
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=ES(C/H)
M=PT(LS)=PS(LS)
M=PC(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=ES(C/H)
M=PT(LS)=PS(LS)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=ES(C)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PT(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PC(LS)=PS(LS)*
M=ES(H)=PC(VL)=PT(VL)=PS(VL)
M=PC(VL)=PS(VL)
M=PT(MLL)=PS(LL)
M=PC(LS)=PS(LS)*
M=PC(VL)=PS(VL)
M=PT(MVL)=PS(VL)
M=PC(LS)=PS(LS)*
M=PT(MVL)=PS(VL)
M=PC(LS)=PS(LS)*
M=ES(C/H)
M=PT(LS)=PS(LS)
M=PT(MLL)=PS(LL)
M=PC(LS)=PS(LS)*
M=ES(C/H)
M=PT(LS)=PS(LS)
Level 3
Page 244
Appendices
224
G.4: Selected list of generated feasible flowsheet alternatives
Level 1 --DEFGIJ-- DEFGI/J DF/GE E/G
149 Fermentation Centrifugation Flash Crystallization
157 Fermentation Centrifugation Liquid-liquid membrane Crystallization
165 Fermentation Centrifugation Pervaporation membrane Crystallization
173 Fermentation Centrifugation Distillation Crystallization
181 Fermentation Centrifugation Crystallization Crystallization --DEFGIJ-- DEFGI/J DFE/G E/G
185 Fermentation Centrifugation Flash Crystallization
186 Fermentation Centrifugation Liquid-liquid membrane Crystallization
187 Fermentation Centrifugation Pervaporation membrane Crystallization
188 Fermentation Centrifugation Distillation Crystallization
189 Fermentation Centrifugation Crystallization
190 Fermentation Centrifugation Extractive distillation Crystallization
191 Fermentation Centrifugation Liquid-liquid extraction Crystallization
192 Fermentation Centrifugation Adsorption (MSA(S)) Crystallization
Level 2a --DEFGIJ—DEFGI/J-- DF/GE E/G
405 Membrane bio-reactor Flash Crystallization
413 Membrane bio-reactor Liquid-liquid membrane Crystallization
421 Membrane bio-reactor Pervaporation membrane Crystallization
429 Membrane bio-reactor Distillation Crystallization
437 Membrane bio-reactor Crystallization Crystallization --DEFGIJ-- DEFGI/J-- DFE/G E/G
441 Membrane bio-reactor Flash Crystallization
442 Membrane bio-reactor Liquid-liquid membrane Crystallization
443 Membrane bio-reactor Pervaporation membrane Crystallization
444 Membrane bio-reactor Distillation Crystallization
445 Membrane bio-reactor Crystallization
446 Membrane bio-reactor Extractive distillation Crystallization
447 Membrane bio-reactor Liquid-liquid extraction Crystallization
448 Membrane bio-reactor Adsorption (MSA(S)) Crystallization
Level 2b --DEFGIJ-- DEFGI/J DF/GE--E/G
571 Fermentation Centrifugation Flash crystallization
575 Fermentation Centrifugation Membrane (pervaporation) crystallization
576 Fermentation Centrifugation Membrane (liquid-liquid) crystallization
581 Fermentation Centrifugation Adsorptive crystallization
Page 245
Appendices
225
Level 2c
--DEFGIJ-- DEFGI/J D/FGE F/GE--E/G
667 Fermentation Centrifugation Distillation Membrane (pervaporation) crystallization
668 Fermentation Centrifugation Distillation Membrane (liquid-liquid) crystallization --DEFGIJ—DEFGI/J-- D/FGE F/GE--E/G
723 Membrane bio-reactor Distillation Membrane (pervaporation) crystallization
724 Membrane bio-reactor Distillation Membrane (liquid-liquid) crystallization
Level 3a
--DEFGIJ-- DEFGI/J D/FGE--F/EG--E/G
766 Fermentation Centrifugation Flash membrane (liquid-liquid) crystallization
767 Fermentation Centrifugation Flash membrane (pervaporation) crystallization
772 Fermentation Centrifugation Adsorptive membrane (pervaporation) crystallization
773 Fermentation Centrifugation Adsorptive membrane (liquid-liquid) crystallization
Level 3a
--DEFGIJ--DEFGI/J D/FGE--F/EG--E/G
776 Membrane bio-reactor Flash membrane (liquid-liquid) crystallization
777 Membrane bio-reactor Flash membrane (pervaporation) crystallization
782 Membrane bio-reactor Adsorptive membrane (pervaporation) crystallization
783 Membrane bio-reactor Adsorptive membrane (liquid-liquid) crystallization
Level 3b --DEFGIJ-- DEFGI/J-- DFE/G--S*/G E/G
784 Membrane bio-reactor Extractive membrane (liquid-liquid) distillation Crystallization
785 Membrane bio-reactor Extractive membrane (pervaporation) distillation Crystallization
786 Membrane bio-reactor Extractive divided wall column Crystallization
787 Membrane bio-reactor Membrane liquid-liquid extraction Crystallization
788 Membrane bio-reactor Membrane(pervaporation) liquid-liquid extraction Crystallization
789 Membrane bio-reactor Extractive (liquid-liquid) distillation Crystallization
Page 246
Department of Chemical and Biochemical Engineering Technical University of Denmark
Søltofts Plads, Building 2292800 Kgs. LyngbyDenmarkPhone: +45 45 25 28 00
www.kt.dtu.dk