Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering explores effective modeling and simulation approaches for solving equations. Using a systematic treatment of model development and simulation studies for chemical, biochemical, and environmental processes, this book explains the simplification of a complicated process at various levels with the help of a "model sketch."
It introduces several types of models, examines how they are developed, and provides examples from a wide range of applications. This includes models based on simple laws such as Fick’s law, models that consist of generalized equations such as equations of motion, discrete-event models and stochastic models (which consider at least one variable as a discrete variable), and models based on population balance.
Divided into 11 chapters, this book:
- Presents a systematic approach of model development in the view of the simulation need
- Includes modeling techniques to model hydrodynamics, mass and heat transfer, and reactors for single as well as multiphase systems
- Provides stochastic and population balance models
- Covers the application and development of artificial neural network models and hybrid ANN models
- Highlights gradients-based techniques as well as statistical techniques for model validation and sensitivity analysis
- Contains examples on the development of analytical, stochastic, numerical, and ANN-based models as well as simulation studies using them
- Illustrates modeling concepts with a wide spectrum of classical as well as recent research papers
Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering includes recent trends in modeling and simulation, such as artificial neural network (ANN)-based models and hybrid models. In addition, a set of MATLAB code files for the chapter examples are available in an appendix.