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Process modeling is one of the key aspects of process systems engineering. It is a significant activity in most major companies around the world, driven by applications such as process optimization, design, and control.Process Modeling and Modeling Analysis gives a comprehensive treatment of process modeling for the student, researcher, and industrial practitioner. It presents a systematic approach to modeling covering model formulation, documentation, analysis, solution, and validation. Process models depend not only on the process itself, but also on the modeling goal. This book, therefore, places its main emphasis on process models for dynamic simulation and process control purposes.This book:* 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 Ian Cameron is Reader in Chemical Engineering at the University of Queensland with teaching, research, and consultancy interests in process systems engineering. He has a particular interest in process modeling, dynamic simulation, and the application of advanced numerical methods to large-scale process systems. He has developed innovative courses in process modeling, design, and 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 problems, as well as the development of internet-based tools for process systems applications.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. |
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