This book 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
1. Introduction 2. I: Fundamental Principles and Process Model Development 3. Chapter 1: The Role of Models in Process Systems Engineering 4. Chapter 2: A Systematic Approach to Model Building 5. Chapter 3: Conservation Principles 6. Chapter 4: Constitutive Relations 7. Chapter 5: Dynamic Models—Lumped Parameter Systems 8. Chapter 6: Solution Strategies for Lumped Parameter Models 9. Chapter 7: Dynamic Models-Distributed Parameter Systems 10. Chapter 8: Solution Strategies for Distributed Parameter Models 11. Chapter 9: Process Model Hierarchies 12. II: Advanced Process Modelling and Model Analysis 13. Chapter 10: Basic Tools for Process Model Analysis 14. Chapter 11: Data Acquisition and Analysis 15. Chapter 12: Statistical Model Calibration and Validation 16. Chapter 13: Analysis of Dynamic Process Models 17. Chapter 14: Process Modelling for Control and Diagnostic Purposes 18. Chapter 15: Modelling Discrete Event Systems 19. Chapter 16: Modelling Hybrid Systems 20. Chapter 17: Modelling Applications in Process Systems 21. Chapter 18: Computer Aided Process Modelling 22. Chapter 19: Empirical Model Building 23. Appendix: Basic Mathematical Tools 24. Bibliography 25. Index
This book 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
1. Introduction 2. I: Fundamental Principles and Process Model Development 3. Chapter 1: The Role of Models in Process Systems Engineering 4. Chapter 2: A Systematic Approach to Model Building 5. Chapter 3: Conservation Principles 6. Chapter 4: Constitutive Relations 7. Chapter 5: Dynamic Models—Lumped Parameter Systems 8. Chapter 6: Solution Strategies for Lumped Parameter Models 9. Chapter 7: Dynamic Models-Distributed Parameter Systems 10. Chapter 8: Solution Strategies for Distributed Parameter Models 11. Chapter 9: Process Model Hierarchies 12. II: Advanced Process Modelling and Model Analysis 13. Chapter 10: Basic Tools for Process Model Analysis 14. Chapter 11: Data Acquisition and Analysis 15. Chapter 12: Statistical Model Calibration and Validation 16. Chapter 13: Analysis of Dynamic Process Models 17. Chapter 14: Process Modelling for Control and Diagnostic Purposes 18. Chapter 15: Modelling Discrete Event Systems 19. Chapter 16: Modelling Hybrid Systems 20. Chapter 17: Modelling Applications in Process Systems 21. Chapter 18: Computer Aided Process Modelling 22. Chapter 19: Empirical Model Building 23. Appendix: Basic Mathematical Tools 24. Bibliography 25. Index
