Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Classification
- 3 Model formulation
- 4 Empirical model building
- 5 Strategies for simplifying mathematical models
- 6 Numerical methods
- 7 Statistical analysis of mathematical models
- Appendix A Microscopic transport equations
- Appendix B Dimensionless variables
- Appendix C Student’s t-distribution
- Bibliography
- Index
Preface
Published online by Cambridge University Press: 05 June 2014
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Classification
- 3 Model formulation
- 4 Empirical model building
- 5 Strategies for simplifying mathematical models
- 6 Numerical methods
- 7 Statistical analysis of mathematical models
- Appendix A Microscopic transport equations
- Appendix B Dimensionless variables
- Appendix C Student’s t-distribution
- Bibliography
- Index
Summary
The aim of this textbook is to give the reader insight and skill in the formulation, construction, simplification, evaluation/interpretation, and use of mathematical models in chemical engineering. It is not a book about the solution of mathematical models, even though an overview of solution methods for typical classes of models is given.
Models of different types and complexities find more and more use in chemical engineering, e.g. for the design, scale-up/down, optimization, and operation of reactors, separators, and heat exchangers. Mathematical models are also used in the planning and evaluation of experiments and for developing mechanistic understanding of complex systems. Examples include balance models in differential or integral form, and algebraic models, such as equilibrium models.
The book includes model formulation, i.e. how to describe a physical/chemical reality in mathematical language, and how to choose the type and degree of sophistication of a model. It is emphasized that this is an iterative procedure where models are gradually refined or rejected in confrontation with experiments. Model reduction and approximate methods, such as dimensional analysis, time constant analysis, and asymptotic methods, are treated. An overview of solution methods for typical classes of models is given. Parameter estimation and model validation and assessment, as final steps, in model building are discussed. The question “What model should be used for a given situation?” is answered.
- Type
- Chapter
- Information
- Mathematical Modeling in Chemical Engineering , pp. ix - xPublisher: Cambridge University PressPrint publication year: 2014