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Computation of mathematical models for complex industrial processes /
Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numer...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hackensack, NJ :
World Scientific Publishing Co. Inc.,
2014.
|
| Colección: | Advances in process systems engineering ;
v. 4. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 1. Introduction. 1.1. Background. 1.2. Motivation. 1.3. Process modelling. 1.4. Model approximation. 1.5. Algorithm design and setup. 1.6. Interpretation of verification of computing results. 1.7. Book outline
- 2. Fundamentals of process modelling and model computation. 2.1. Building mathematical models. 2.2. General ODE and PDE models for industrial processes. 2.3. Examples of ODE and PDE process models. 2.4. Solutions of process models. 2.5. The Runge-Kutta methods. 2.6. Finite difference methods. 2.7. Wavelets-based methods. 2.8. High resolution methods
- 3. Finite difference methods for ordinary differential equation models. 3.1. Fermentation processes. 3.2. Biology of lysine synthesis. 3.3. Model construction. 3.4. Numerical approximations of fermentation models. 3.5. Simulation for Batch fermentation. 3.6. Simulation for Fed-Batch fermentation
- 4. Finite difference methods for partial differential equation models. 4.1. Continuous galvanizing processes. 4.2. Development of a PDE model. 4.3. Discrete state space model. 4.4. Stability analysis and parameter settings of the model. 4.5. Identification of model parameters. 4.6. Least-square algorithms for system identification. 4.7. Simplification of system identification algorithms. 4.8. Simulations and industrial applications
- 5. Wavelets-based methods. 5.1. Process modelling for chemical reactions. 5.2. Three versions of wavelet collocation methods. 5.3. Wavelet collocation method for reaction processes. 5.4. Model development for crystallization processes. 5.5. Wavelet Galerkin method for PDEs. 5.6. Solution based on wavelet Galerkin method
- 6. High resolution methods. 6.1. Column chromatographic separation processes. 6.2. Model development for column chromatography. 6.3. Analytical solution for linear equilibrium case. 6.4. Model discretization using high resolution methods. 6.5. The Alexander method for time integration. 6.6. Solutions to the chromatographic process model. 6.7. Crystallization and population balance equations. 6.8. Crystallization with pure size-independent growth. 6.9. Process with size-independent growth and nucleation
- 7. Comparative studies of numerical methods for SMB chromatographic processes. 7.1. Chromatographic separation processes. 7.2. Dynamic modelling of SMBC processes. 7.3. Numerical computation. 7.4. Case study I: Fructose-glucose separation. 7.5. Case study II: Bi-naphthol enantiomers separation. 7.6. Concluding remarks
- 8. Conclusion.