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.