Modelling of Chemical Process Systems

by Syed Ahmad Imtiaz (Editor)

Overview

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

Product Details

ISBN-13:	9780128241998
Publisher:	Elsevier Science
Publication date:	07/25/2023
Sold by:	Barnes & Noble
Format:	eBook
Pages:	312
File size:	30 MB
Note:	This product may take a few minutes to download.

About the Author

Dr. Imtiaz received his PhD (University of Alberta) degrees in Chemical Engineering. After completing his PhD degree, he worked as a Staff Consultant at Aspen Technology implementing advanced control systems for refineries, ethylene plants, methanol plants, and petro-chemical plants. He has implemented over thirty unit-wide model predictive controllers.He joined Memorial University as an Assistant Professor in 2010, promoted to Associate Professor in 2016. Currently he is the Head of the Department in Process Engineering at Memorial University. His research interests involve process monitoring, control systems, modelling, and alarm management. He teaches several graduate and undergraduate level including undergraduate course on Process Modelling and Model Analysis. He has published over 80 journal and conference articles in these fields. He holds several research grants including NSERC Discovery Grant. He is also a recipient of Imperial Oil University Research Award.

Table of Contents

Part I Theory and Background1. Introduction to process modelling2. Model equations and modelling methodology Part II Micro Scale Modelling3. Density functional theory (DFT) models for extraction of sulfur compounds from fuel oils by using ionic liquids4. Molecular dynamics simulation in energy and chemical systems5. Single event modelling of reaction kinetics6. Modelling and simulation of batch and continuous crystallization processes Part III Macro Scale Modelling of Process Systems7. Fuel processing systems8. Crude to chemicals: Conventional FCC unit still relevant Part IV Machine Learning Techniques for Modelling Process Systems9. Hybrid model for a diesel cloud point soft-sensor 10. Large-scale process models using deep learning

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From the Publisher

Step-by-step methodology for building chemical process systems models