Stochastic Process Optimization using Aspen Plus®

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.

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.

1. Introduction to optimization. 2. Deterministic optimization. 3. Stochastic optimization. 4. The simulator Aspen Plus. 5. Direct optimization in Aspen Plus. 6. Optimization using Aspen Plus and a stochastic toolbox. 7. Using an external user defined block model in Aspen Plus. 8. Optimization with a user kinetic model. 9. Optimization of a biobutanol production process. 10. Optimization of a silane production process.