224 pages | 40 Color Illus. | 148 B/W Illus.
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.
• 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.
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
Chapter 2 Deterministic optimization
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
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
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
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
Chapter 6 Optimization using Aspen Plus and a stochastic toolbox
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
Chapter 7 Using an external user defined block model in Aspen Plus
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
Chapter 8 Optimization with a user kinetic model
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
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
Chapter 10 Optimization of a silane production process
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