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Product and Process Modelling
A Case Study Approach
Ian T. Cameron (Author), Rafiqul Gani (Author)
9780444531612
Hardback, published 13 July 2011
548 pages
22.9 x 15.1 x 3.2 cm, 1.03 kg
"This book takes the reader on an exciting journey of practical case studies. It provides an exemplary illustration of the crucial role of systematic approaches for the goal-oriented development of mathematical models of complex process systems. This is a high quality contribution from leaders in the field, a must-have book for any modeling practitioner. It fills an important gap among other well known books in the field that mainly focus on the theory and methodologies required for model development and solution…. This book serves as a highly valuable resource of complex models, for graduate students, academics and industrialists." --Chemistry World
This book covers the area of product and process modelling via a case study approach. It addresses a wide range of modelling applications with emphasis on modelling methodology and the subsequent in-depth analysis of mathematical models to gain insight via structural aspects of the models. These approaches are put into the context of life cycle modelling, where multiscale and multiform modelling is increasingly prevalent in the 21st century. The book commences with a discussion of modern product and process modelling theory and practice followed by a series of case studies drawn from a variety of process industries. The book builds on the extensive modelling experience of the authors, who have developed models for both research and industrial purposes. It complements existing books by the authors in the modelling area. Those areas include the traditional petroleum and petrochemical industries to biotechnology applications, food, polymer and human health application areas. The book highlights to important nature of modern product and process modelling in the decision making processes across the life cycle. As such it provides an important resource for students, researchers and industrial practitioners. 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. Rafiqul Gani is a Professor of Systems Design at the Department of Chemical and Biochemical Engineering, Technical University of Denmark, and the director of the Computer Aided Product-Process Engineering Center (CAPEC). His research interests include the development of computer-aided methods and tools for modelling, property estimation and process-product synthesis and design. He received his BSc from Bangladesh University of Engineering and Technology in 1975, and his MSc in 1976 and PhD in 1980 from Imperial College London. He is the editor-in-chief of Computers and Chemical Engineering journal and Fellow of IChemE as well as AIChE.
1. Modelling: Nature and Use2. Modelling Practice3. Computer Aided Modelling Tools4. Case Studies: Overview5. Constitutive Models5.1. Constitutive Models – Physical properties5.2. Constitutive Model Parameter Estimation5.3. Constitutive Model Applications6. Steady State Process Modelling6.1. Equation based approach6.2. Simulator based modelling7. Models for Dynamic Application7.1. Complex unit operations – Blending tank7.2. Complex integrated operation: Direct methanol fuel cell7.3. Multiscale fluidized bed reactor7.4. Dynamic chemical reactor7.5. Polymerization reactor8. Distributed Parameter Modelling Applications8.1. Oil-shale pre-heating cooling unit8.2. Modelling the dynamic performance of a complex granulator8.3. Short-path evaporator model9. Tennessee Eastman Plant-wide Industrial Process Challenge Problem 9.1. Simplified model9.2. Full model10. Batch Process Operations10.1. Batch cooling crystallization modelling (population balance modelling)10.2. Batch event modelling11. Model Identification (Parameter Estimation)11.1. Modelling of simple reaction kinetics11.2. Kinetic model parameter estimation -1 (least squares)11.3. Kinetic model parameter estimation -2 (non-linear least squares)11.4. Kinetic model parameter estimation -3 (model identification)11.5. Kinetic model parameter estimation (maximum likelihood principle)12. Modelling for Bio, Agro and Pharma Applications12.1. Microcapsule based controlled release12.2. Fermentation process12.3. Milk pasteurization process12.4. Milling process model12.5. Granulation process model12.6. Pharmaceutical tablet pressing process13. Future Perspectives14. Appendix 14.1. Appendix-114.2. Appendix-2
Subject Areas: Chemical engineering [TDCB], Industrial chemistry [TDC]
