PROCESS SYSTEMS ENGINEERING GROUP

PROCESS SYSTEMS ENGINEERING GROUP

FørsteamanuensisTore Haug-Warberg

ProfessorHeinz Preisig

ProfessorSigurd Skogestad

FørsteamanuensisNadi Skjøndal-Bar

• Process modelling• Including thermodynamic modelling

• Process optimization and control• Process simulation and design• Systems biology

Professor IIKrister Forsman,

Perstorp

1 postdoc5 PhD students 16 Master students

Modeling and control

• Very useful and general knowledge– Can be used for everything

• Wide range of applications and job opportunities:– “Usual” process companies (Statoil…)

+ Siemens, ABB, Cybernetica, software companies + +

CORE SUBJECTS PROCESS SYSTEMS ENGINEERING

•Modelling•Optimization•Simulation, computation & programming•Control & operation•Design & synthesis

• Subjects expected to remain relevant and growing in importanceover the next 50 years +

4th year courses

Autumn:TKP4140* Process control (Prosessregulering)

Spring:TKP4135 Chemical process systems engineeringTKP4195 System modellering og analyse i Biologi

Also recommended spring:TTK4135 Optimalisering og regulering (tekn.kyb.)

5th year courses, autumn

TKP4555 PROCESS- SYSTEM ENGINEERING specialization

Select two modules from the following:• TKP10 Process Control, Advanced Course• TKP11 Advanced Process Simulation• TKP12 Thermodynamics, Advanced Course• TKP13 Feedback systems in biology

It is also possible to select other modules, but this has to be approved in advance.

Examles: TKPX Kjemisk prosessteknologi, spesielle emner (distillation) TTK16 Modellprediktiv regulering (MPC) og optimalisering (Institutt for teknisk kybernetikk) TEP9 Termisk kraft/varme - produksjon (Institutt for termisk energi og vannkraft)

TKP10 Process Control, Advanced Course

• Lecturer: Professor Sigurd Skogestad

• Learning outcome : Be able to design plantwide control system

• Content: – Control structure design for complete chemical plants. – Selection of controlled variables (self-optimizing control).– Consistent inventory Control.– Regulatory control.– Tuning of PID controllers.– Multivariable control.– Decentralized control.– RGA. Introduction to MPC. Use of dynamic simulators.

• Teaching activities: Lectures, computer simulation. exercises. • Course material: Copies from scientific papers and books including Chapter

10 in Skoegstad and Postlethwaite, "Multivariable Feedback Control, Wiley, 2010

TKP11 Advanced Process Simulation

• Lecturer: Professor Heinz Preisig

• Contents: Simulators solve sets of equations representing the behaviour of plants, namely mathematical models for the plant. The topic of the course is to shed some light on what is under the hood of these simulators.

– The subject is extended by optimisers which are superimposed on the simulators upwards and physical property interfaces downwards.

– The course touches on the theoretical subjects associated with the methods used in simulators and optimisers, such as graph theory for the representation of networks, sequential modular approaches and simultaneous equation approaches and possibly integrators.

• Course form: Lectures, tutorials and project. The course is largely project oriented.

• Prerequisites: Course in numerics, optimisation and preferably TKP4135 Chemical Process Systems Engineering

• Compulsory activities: exercises, presentations, project work

TKP12 Thermodynamics, Advanced Course

• Lecturer: Associate professor Tore Haug-Warberg• Content:

– Thermodynamic methods (Euler functions and Legendre transformations) with applications to thermodynamic state theory.

– Systematic derivation of basic equations in canonical state variables.– Conservation principles of mass and energy used in the analysis of

practical problem solutions connected to phase and reaction equilibria.– Introduction to thermodynamic modelling. – The course is adapted to individual needs if feasible (more weight on the

modelling and less weight on the problem analysis, or vice versa).• Teaching activities: Regular teaching and colloquiums.• Course material: Lecture notes and copies of articles.

TKP13 Feedback systems in biology

• Lecturer: Associate Professor Nadi Skjøndal-Bar• Aim of the course: To present the concept of feedback in relation to

biological intra- and intercellular processes• Prerequisites: TKP4140 process control or equivalent knowledge in control• Module description: The concept of feedback is well known from control

theory, and is quite abundant in biology. – Concept of negative and positive feedback inside the cells and in genetic circuits.– Cellular response to combinations such as negative-negative, positive-negative

feedback structures– Oscillations and bi-stability– Effect of feedback on the evolution of species.

• Teaching methods: Seminars, self study, exercises/project work with presentations.

• Course material: Articles and excerpts from textbooks.

Sigurd SkogestadResearch projects 2014

69. Modelling and optimization of compact subsea separators70. Modelling and optimization of a 2-stage compressor train71. Optimization using ideas from self-optimizing control72. Dynamics and plantwide control of the Dynea silver formaldehyde process73. Optimal location of the throughput manipulator74. Alternative implementations of midranging control75. Expected problems when pairing on negative RGA-elements75b. New method for temporary heating or cooling with minimal energy consumption and CO2 emission (with Harald Martens)

Projects Krister Forsman76. Cascade control

77. Implementation of ratio control

78. Variance minimizing control

79. Industrial control case at Perstorp

Nadi Skjøndal-BarResearch projects

80. Simulation and numerical optimization of a dynamic model of model of growth (System biology: applied modelling81. Modeling and simulations of bat flight and sonar in 3-dimensions (Systems biology: Neuroscience). 82. Modeling and simulation of path -finding and tracking, applied to ants

Heinz PreisigResearch projects

83. Temperature distribution in milli-reactor, CFD-simulations84. Residence-time distribution in various mixed systems, CFD Simulations85. Nonlinear experiment design86. Ontology for material models87. SINTEF Bio-Refinery Pretreatment of marine biomass88. Continuous distillation89. Chemical Engineering ontology for standard reactor types90. CAPE-OPEN interface to unit simulations91. Computer-aided modelling 92. Control and Felles lab rejuvenation93. Automatic Safety and Hazard Analysis94. Simple Thermo Server (with Tore Haug-Warberg)95. On time scaling in chemical processes96. Frequency Analysis of Distillation97. Process Identification using Wavelets 98. Felles lab new suggested experiment: colloid chemistry experiment

Species dataReaction data

Model LibraryDocumentation

MatLab DAE

Model

MODELLER

MatLabMatLab LibraryGraph of BehaviourData of Behaviour

Equation Library

Tore Haug-WarbergResearch projects 2013

1. Thermodynamics of LNG using the GERG equation of state.

2. Taylor-expansion of thermodynamic equilibrium states arising from flash calculations.

3. Validation of thermodynamic state calculations in Brilliant (Petrell).

4. Code wrappers in Python, Ruby, Lua for thermodynamic utility software (SINTEF).

5. Advanced mass balances of zink refinery (Boliden-Odda).

Some recent PhD graduates (and where they work)• Federico Zenith, Control of fuel cells, June 2007 (SINTEF Cybernetics, Trondheim) • Jørgen B. Jensen, Optimal operation of refrigeration cycles, May 2008 (ABB, Oslo)• Heidi Sivertsen, Stabilization of desired flow regimes using active control, December 2008 (Statoil, Stjørdal) • Elvira M.B. Aske, Design of plantwide control systems with focus on maximizing throughput, March 2009 (Statoil

Research, Trondheim) • Andreas Linhart, An aggregation model reduction method for one-dimensional distributed systems, Oct. 2009 (Conergy AG,

Hamburg). • Henrik Manum, Simple implementation of optimal control for process systems, Nov. 2010 (Statoil Research, Trondheim). • Jens P. Strandberg, Optimal operation of dividing wall columns, June 2011 (Aker Solutions, Oslo). • Johannes Jäschke, Invariants for optimal operation of process systems, June 2011 (postdoc, NTNU, Trondheim). • Magnus Glosli Jacobsen, Identifying active constrain regions for optimal operation of process plants, Nov. 2011 (ABB, Oslo). • Mehdi Panahi, Plantwide control for economically optimal operation of chemical plants - Application to GTL plants and CO2

capturing processes, Dec. 2011 (Aker Solutions, Oslo). • Ramprasad Yelchuru, Quantitative methods for controlled variable selection, June 2012 (ABB, Oslo). • Deeptanshu Dwivedi, Control and operation of dividing-wall columns with vapor split manipulation, Jan. 2013 (ABB, Oslo). • Esmaeil Jahanshahi, Control solutions for multiphase flow: Linear and nonlinear approaches to anti-slug control, Oct. 2013.

(Siemens, Trondheim)

Conclusion: Welcome to K4 – 2nd floor!