Stochastic Process Optimization using Aspen Plus®: 1st Edition (Hardback) book cover

Stochastic Process Optimization using Aspen Plus®

1st Edition

By Juan Gabriel Segovia-Hernández, Fernando Israel Gómez-Castro

CRC Press

224 pages | 40 Color Illus. | 148 B/W Illus.

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Hardback: 9781498785105
pub: 2017-08-28
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Description

Stochastic Process Optimization using Aspen® Plus

Bookshop Category: Chemical Engineering

Optimization can be simply defined as "choosing the best alternative among a set of feasible options". In all the engineering areas, optimization has a wide range of applications, due to the high number of decisions involved in an engineering environment. Chemical engineering, and particularly process engineering, is not an exception; thus stochastic methods are a good option to solve optimization problems for the complex process engineering models.

In this book, the combined use of the modular simulator Aspen® Plus and stochastic optimization methods, codified in MATLAB, is presented. Some basic concepts of optimization are first presented, then, strategies to use the simulator linked with the optimization algorithm are shown. Finally, examples of application for process engineering are discussed.

The reader will learn how to link the process simulator Aspen® Plus and stochastic optimization algorithms to solve process design problems. They will gain ability to perform multi-objective optimization in several case studies.

Key Features:

• The book links simulation and optimization through numerical analyses and stochastic optimization techniques

• Includes use of examples to illustrate the application of the concepts and specific guidance on the use of software (Aspen® Plus, Excel, MATLB) to set up and solve models representing complex problems.

• Illustrates several examples of applications for the linking of simulation and optimization software with other packages for optimization purposes.

• Provides specific information on how to implement stochastic optimization with process simulators.

• Enable readers to identify practical and economic solutions to problems of industrial relevance, enhancing the safety, operation, environmental, and economic performance of chemical processes.

Table of Contents

Chapter 1 Introduction to optimization

1.1 What is optimization?

1.2 Mathematical modelling and optimization

1.3 Classification of optimization problems

1.4 Objective function

1.5 Optimization with constraints: feasible region

1.6 Multiobjective optimization

1.7 Process optimization

References

Chapter 2 Deterministic optimization

2.1 Introduction

2.2 Single variable deterministic optimization

2.3 Continuity and convexity

2.4 Unconstrained optimization

2.5 Equality-constrained optimization

2.6 Equality and inequality-constrained optimization

2.7 Software for deterministic optimization

References

Chapter 3 Stochastic optimization

3.1 Introduction to stochastic optimization

3.2 Stochastic optimization vs deterministic optimization

3.3 Stochastic optimization with constraints

3.4 Genetic algorithms

3.5 Differential evolution

3.6 Tabu search

3.7 Simulated annealing

3.8 Other methods

References

Chapter 4 The simulator Aspen Plus

4.1 Importance of software for process analysis

4.2 Characteristics of the process simulator Aspen Plus

4.3 Sequential modular simulation

References

Chapter 5 Direct optimization in Aspen Plus

5.1 Optimization methods

5.2 Sensitivity analysis tools in Aspen Plus

5.3 Sequential quadratic programming (SQP) in Aspen Plus

5.4 Optimization of a heat exchanger

5.5 Optimization of a flash drum

5.6 Optimization of a tubular reactor

References

Chapter 6 Optimization using Aspen Plus and a stochastic toolbox

6.1 Introduction

6.2 Software for stochastic optimization

6.3 Linking Aspen Plus with the stochastic optimization software

6.4 Mono-objective optimization of a multicomponent distillation column

6.5 Multi-objective optimization of a multicomponent distillation column

6.6 Conclusions

References

Chapter 7 Using an external user defined block model in Aspen Plus

7.1 Introduction

7.2 Importance of the user defined block models

7.3 Previous work and loading a user defined block model in Aspen Plus

7.4 Linking the user defined block model with Microsoft Excel and Matlab

7.5 Conclusions

References

Chapter 8 Optimization with a user kinetic model

Introduction

8.1 Kinetic models allowed in Aspen Plus

8.2 Developing a user kinetic model

8.3 Loading a user kinetic model in Aspen Plus

8.4 Optimization of a reactive distillation column with a user kinetic model

8.5 Reactive distillation column with a default kinetic model

8.6 Conclusions

References

Chapter 9 Optimization of a biobutanol production process

9.1 Description of the process

9.2 Thermodynamics and kinetic model

9.3 Optimization process

9.4 Optimization results

9.5 Conclusions

References

Chapter 10 Optimization of a silane production process

10.1 Introduction

10.2 Silane production

10.3 Description of the process using reactive distillation

10.4 Economic potential of reactive distillation production of silane

10.5 Thermodynamics and kinetic model

10.6 Initial designs

10.7 Process optimization

10.8 Conclusions

References

About the Authors

Juan Gabriel Segovia-Hernández

Prof. Segovia-Hernández has been with University of Guanajuato, Mexico, since 2004, in the Chemical Engineering Department. He has co-edited one book and published over 110 papers in international journals, 8 book chapters and several refereed conference proceedings. He was national president of Mexican Academy of Chemical Engineering (2013-2015). He is Member of Mexican Academy of Sciences since 2012. His research interests include design, optimization and control of intensified processes. He is currently the lecturer in several universities in México and abroad. For more details on his research and publications, browse https://www.segovia-hernandez.com

Fernando Israel Gómez-Castro

Professor in the Chemical Engineering Department of the University of Guanajuato since 2012. Obtained the degree of ScD in Chemical Engineering in 2010 at the Institute of Technology of Celaya, Mexico. Author of 31 research papers published in national and international journals and 5 chapters of books, and reviewer of international journals as Chemical Engineering & Technology, Chemical Engineering Research & Design, Industrial & Chemistry Engineering Research, Fuel, among others. Member of the National Researchers System (Mexico) and the American Chemical Society. Its biography has appeared in directories as "Who’s Who in the World" and "2000 Outstanding Intellectuals of the 21st Century". He is currently the lecturer of subjects associated with mathematical optimization and its application to chemical process design, for both bachelor and graduate levels. Among his research interests it can be mentioned the use of computational tools for the design and optimization of conventional and intensified chemical processes.

Subject Categories

BISAC Subject Codes/Headings:
MAT003000
MATHEMATICS / Applied
SCI013060
SCIENCE / Chemistry / Industrial & Technical