Modelling of Chemical Process Systems gives readers a feel for multiscale modeling. The book starts with the history of modeling and its usefulness, describing modeling steps in detail. Examples have been chosen carefully from both conventional chemical process systems to contemporary systems, including fuel cell and micro reforming processes. Each chapter is accompanied by a case study that explains the step-by-step modeling methodology. The book also introduces the application of machine learning techniques to model chemical process systems. When combined, the information in the book makes it an indispensable reference for academics and professionals working in modeling and simulation. Includes case studies that explain step-by-step modeling methodologies Covers detailed multiscale modeling of chemical processes, providing examples from traditional and novel areas Provides modeling at microscopic and macroscale levels, including machine learning techniques INDICE: Part I Theory and Background 1. Introduction to Process Modelling 2. Model Equations and Modelling Methodology Part II Micro Scale Modelling 3. Density functional theory (DFT) models for extraction of sulfur compounds from fuel by using ionic liquids 4. Molecular dynamics simulation in chemical, and energy systems 5. Single Event Modelling of Reaction Kinetics 6. Modelling and simulation of batch and continuous crystallization processes Part III Macro Scale Modelling of Process Systems 7. Crude to Chemicals: Conventional FCC Unit Still Relevant 8. Modelling and simulation of solid oxide fuel cells 9. Fuel Reforming for Fuel Cells Part IV Machine Learning Techniques for Modelling Process Systems 10. Supervised Learning Algorithms for Process Modelling 11. Large-Scale Process Models using Deep Learning
- ISBN: 978-0-12-823869-1
- Editorial: Elsevier
- Encuadernacion: Rústica
- Páginas: 312
- Fecha Publicación: 03/05/2022
- Nº Volúmenes: 1
- Idioma: Inglés