Yulong Liu 2012.11.23 Journal Club Process Simulation and Multiobjective Optimization
Jan 12, 2016
Yulong Liu
2012.11.23
Journal Club
Process Simulation and
Multiobjective Optimization
Process Simulation Based on Experimental
Investigations for 3‑Methylthiophene Alkylation
with Isobutylene in a Reactive Distillation Column
Yu Liu, Bolun Yang*, and Shasha Li
Department of Chemical Engineering, State Key Laboratory of Multiphase Flow
in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, P.R. China
Ind. Eng. Chem. Res. 2012, 51, 9803−9811
Introduction
The key design factors (number of reactive and nonreactive
stages, location of feed stage, column pressure, mass ratio of
distillate to feed, and catalyst weight) were optimized.
Higher alkylation selectivity , better catalytic stability and the
sulfur content in FCC gasoline declined by more than 99%.
Equipment and Procedures
Number of Reaction Stages
The reaction stage number of 5 was used in further simulation studies.
Number of Rectifying Stages and Stripping Stages
The rectifying zone of 5 stage was considered in the further simulations
The stripping zone of 1 stage was considered in the further simulations
Column Pressure
A pressure of 0.2 MPa would give the reflux drum temperature of about
325 K; cooling water thus can be used in the condenser in this case.
Feed Location and Catalyst Weight
The residence time of 3MT in reaction zone was reduced.
The residence time of IB in reaction zone was increased.
Reflux Ratio
Mass Ratio of Distillate to Feed
To limit the reboiler duty and to control the sulfur content (less than 10
ppmw) in distillate stream, a D/F ratio of 0.85 was applied during the
simulations.
Realistic Models for Distillation Columns with
Partial Condensers Producing Both Liquid and
Vapor Products
William L. Luyben*
Department of Chemical Engineering Lehigh University Bethlehem,
Pennsylvania 18015, United States
Ind. Eng. Chem. Res. 2012, 51, 8334−8339
Introduction
This paper demonstrates a realistic way to model a partial
condenser distillation system using Aspen simulation.
Fixing reflux-drum temperature and selecting a reasonable
pressure determines the split between the amount of vapor
product and the amount of liquid product.
In the operation of these systems , we usually want to
condense as much as possible so as to minimize compression
costs of dealing with the vapor product.
Column flowsheet
Feed Flow Rate Disturbances
The realistic situation is when the cooling water flow rate is fixed.
Feed Composition Disturbances
The realistic situation is when the cooling water flow rate is fixed.
Feed Composition Disturbances
The most realistic predictions are those given by the Fixed CW model.
Multiobjective Evolutionary Optimization of
Batch Process Scheduling Under Environmental
and Economic Concerns
Elisabet Capon-Garcia
Dept. of Chemistry and Applied Biosciences, ETH Zurich, Zurich 8093, Switzerland
Aaron D. Bojarski, Antonio Espuna, and Luis Puigjaner
Dept. of Chemical Engineering, CEPIMA, Universitat Politecnica de Catalunya, ETSEIB,
Barcelona 08028, Spain
AIChE Journal .2012 Vol. 00, No. 0
Introduction
The simultaneous consideration of economic and environmental
objectives in batch production scheduling is today a subject of
major concern.
However, reported computational times were extremely high.
Hence, a hybrid strategy has been developed.
Rigorous local search and Genetic algorithm.
Objective functions
The batch i production process environmental impact (EnvImi) and
batch changeover between i and i` at stage k using cleaning method c
environmental impact (EnvImii`kc).
Batch i product benefits (BPi ) and changeover costs between
batches i and i` using cleaning method c at each stage k (ChCostii`kc).
The binary variable(Xii`c).
Multiobjective genetic algorithm
The scheduling problem is formulated using mathematical
programming tools, but it is solved using a multiobjective
genetic algorithm.