
- 312 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Modelling of Chemical Process Systems
About this book
Models and simulations are widely being used for design, optimization, fault detection and diagnosis, and various other decision-making purposes. Increasingly, models are developed at different scales and levels, all the way from molecular level to the large-scale process systems scale.
Modelling of Chemical Process Systems gives readers a feel for the multiscale modelling. As models have been developed for various applications, a general systematic method for building model has emerged. This book starts with the history of modelling and its usefulness, describing modelling steps in detail. Examples have been chosen carefully from both conventional chemical process systems to contemporary systems, including fuel cell and bioprocesses. Modelling theories are complemented with case studies that explain step-by-step modelling methodologies. This book also introduces the application of machine learning techniques to model chemical process systems. This makes the book an indispensable reference for academics and professionals working in modelling and simulation.
- Includes case studies that explain step-by-step modelling methodologies
- Covers detailed multiscale modelling of chemical processes, providing examples from traditional and novel areas
- Provides modelling insight at micro and macro-scale levels, including machine learning techniques
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Modelling of Chemical Process Systems by Syed Ahmad Imtiaz in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Business Intelligence. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Title of Book
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Part I: Theory and background
- Part II: Micro scale modeling
- Part III: Macro scale modeling of process systems
- Part IV: Machine learning techniques for modeling process systems
- Index