FUNDAMENTAL PRINCIPLES AND PROCESS MODEL DEVELOPMENT
The Role of Models in Process Systems Engineering; A Systematic Approach to Model Building; Conservation Principles; Constitutive Relations; Dynamic Models - Lumped Parameter Systems; Solution Strategies for Lumped Parameter Models; Dynamic Models - Distributed Parameter Systems Solution Strategies for Distributed Parameter Systems; Process Model Hierarchies
ADVANCED PROCESS MODELING AND MODEL ANALYSIS
Basic Tools for Process Model Analysis; Data Acquisition and Analysis; Statistical Model Calibration and Validation; Analysis of Dynamic Process Models; Process Modeling for Control and Diagnostic Purposes; Modeling Discrete Event Systems; Modeling Hybrid Systems; Modeling Applications in Process Systems; Computer Aided Process Modeling; Empirical Model Building; Appendix: Basic Mathematic Tools; Bibliography; Index
Process Modelling and Model Analysis describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents.
To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises.
- Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation
- Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling
- Illustrates the notions, tools, and techniques of process modeling with examples and advances applications
Undergraduate and graduate students in chemical, process, environmental, or control engineering. Professionals engineers in industry and government.
- No. of pages:
- © Academic Press 2001
- 23rd May 2001
- Academic Press
- eBook ISBN:
- Hardcover ISBN:
Imperial College, London, U.K.
Gregory Stephanopoulos is a Professor of Chemical Engineering at MIT. He received his B.S. from the National Technical University of Athens, his M.S. from the University of Florida and his Ph.D. from the University of Minnesota, all in Chemical Engineering. Upon graduation, he joined the Chemical Engineering Faculty of the California Institute of Technology, where he served as Assistant and Associate Professor until 1985. In 1985 he was appointed Professor of Chemical Engineering at MIT where he has been ever since.Stephanopoulos' work has appeared in more than 150 publications and 7 patents. He has been recognized with the Dreyfus Foundation Teacher Scholar Award (1982), Excellence in Teaching Award (1984), and Technical Achievement Award of the AIChE (1984). He has been a Presidential Young Investigator and the Chairman of the Food Pharmaceutical & Bioengineering Division of the American Institute of Chemical Engineers (1992). In 1992 he was a Visiting Professor at the International Research Center for Biotechnology at Osaka University and was elected a Founding Fellow of the American Institute for Medical and Biological Engineering. In 1996 he chaired the first Conference on Metabolic Engineering and gave the inaugural Bayer Lecture on Biochemical Engineering at the University of California at Berkeley. He was honored with the FPBE Division Award at AIChE in 1997.
Massachusetts Institute of Technology, Cambridge, U.S.A.
Ian Cameron is Professor in Chemical Engineering at the University of Queensland with teaching, research, and consulting activities in process systems engineering. He has a particular interest in process modelling, dynamic simulation, and the application of functional systems perspectives to risk management, having extensive industrial experience in these areas. He continues to work closely with industry and government on systems approaches to process and risk management issues. He received his BE from the University of New South Wales (Australia) and his PhD from imperial College London. He is a Fellow of IChemE.
School of Chemical Engineering, University of Queensland, Brisbane, Australia
Katalin Hangos is currently a research professor at the Computer and Automation Research Institute, Hungary. She is one of the few woman professors in process systems engineering with a strong background in systems and control theory and computer science. Dr. Hangos's main interest is dynamic process modeling for control and diagnosis purposes. She is co-author of more than 100 papers on various aspects of modeling and its control applications including nonlinear and stochastic process system models, Petri nets, qualitative, and graph-theoretical models.
Systems and Control Laboratory, Computer and Automation Institute, Hungarian Academy of Sciences, Budapest, Hungary