Practical Chemical Process Optimization

This text provides the undergraduate chemical engineering student with the necessary tools for problem solving in chemical or bio-engineering processes. In a friendly, simple, and unified framework, the exposition aptly balances theory and practice. It uses minimal mathematical concepts, terms, algorithms, and describes the main aspects of chemical process optimization using MATLAB and GAMS. Numerous examples and case studies are designed for students to understand basic principles of each optimization method and elicit the immediate discovery of practical applications. Problem sets are directly tied to real-world situations most commonly encountered in chemical engineering applications. Chapters are structured with handy learning summaries, terms and concepts, and problem sets, and individually reinforce the basics of particular optimization methods. Additionally, the wide breadth of topics that may be encountered in courses such as Chemical Process Optimization, Chemical Process Engineering, Optimization of Chemical Processes, are covered in this accessible text. The book provides formal introductions to MATLAB, GAMS, and a revisit to pertinent aspects of undergraduate calculus. While created for coursework, this text is also suitable for independent study. A full solutions manual is available to instructors who adopt the text for their course.

Applications cover examples encountered in chemical processes: chemical reactors, heat transfer and more Undergraduate practical introduction of optimization theory to chemical and biochemical systems Chapters include an introduction, examples, applications, terms and concepts, case studies, and problem sets

Auteur

Ioannis K. Kookos is Professor in the Department of Chemical Engineering at the University of Patras. His research interests include Synthesis and optimization of biotechnological processes for the production of platform chemicals, modelling of mass transfer in SOFCs, plantwide process design and control structure selection, and synthesis, design and optimization of biofuel production.

Contenu

1. Preliminary concepts and definitions.- 2. Multidimensional unconstrained optimization.- 3. Constrained optimization.- 4. Linear programming.- 5. Integer and Mixed Integer Programming Problems.- 6. Solving optimization problems in GAMS.- 7. Representative optimization problems in chemical engineering solved in GAMS.- Appendix A: Introduction to MATLAB.- Literature and Notes for Further Study.- Index.