Advanced Data Analysis and Modelling in Chemical Engineering - 1st Edition - ISBN: 9780444594853, 9780444594846

Advanced Data Analysis and Modelling in Chemical Engineering

1st Edition

Authors: Denis Constales Gregory S. Yablonsky Dagmar D'hooge Joris W. Thybaut Guy B. Marin
eBook ISBN: 9780444594846
Hardcover ISBN: 9780444594853
Imprint: Elsevier
Published Date: 5th September 2016
Page Count: 414
Tax/VAT will be calculated at check-out Price includes VAT (GST)
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
Price includes VAT (GST)
× DRM-Free

Easy - Download and start reading immediately. There’s no activation process to access eBooks; all eBooks are fully searchable, and enabled for copying, pasting, and printing.

Flexible - Read on multiple operating systems and devices. Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle.

Open - Buy once, receive and download all available eBook formats, including PDF, EPUB, and Mobi (for Kindle).

Institutional Access

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques.

Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development.

Key Features

  • Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve them
  • Summarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily work
  • Includes classical analytical methods, computational methods, and methods of symbolic computation
  • Covers the latest cutting edge computational methods, like symbolic computational methods


Chemical engineers and researchers; PhD students, mathematicians working on topics related to chemical engineering/chemistry

Table of Contents

  • Preface
    • Our Team
  • Chapter 1: Introduction
    • Abstract
    • 1.1 Chemistry and Mathematics: Why They Need Each Other
    • 1.2 Chemistry and Mathematics: Historical Aspects
    • 1.3 Chemistry and Mathematics: New Trends
    • 1.4 Structure of This Book and Its Building Blocks
  • Chapter 2: Chemical Composition and Structure: Linear Algebra
    • Abstract
    • 2.1 Introduction
    • 2.2 The Molecular Matrix and Augmented Molecular Matrix
    • 2.3 The Stoichiometric Matrix
    • 2.4 Horiuti Numbers
    • 2.5 Summary
    • Appendix The RREF in Python
  • Chapter 3: Complex Reactions: Kinetics and Mechanisms – Ordinary Differential Equations – Graph Theory
    • Abstract
    • 3.1 Primary Analysis of Kinetic Data
    • 3.2 Material Balances: Extracting the Net Rate of Production
    • 3.3 Stoichiometry: Extracting the Reaction Rate From the Net Rate of Production
    • 3.4 Distinguishing Kinetic Dependences Based on Patterns and Fingerprints
    • 3.5 Ordinary Differential Equations
    • 3.6 Graph Theory in Chemical Kinetics and Chemical Engineering
  • Chapter 4: Physicochemical Principles of Simplification of Complex Models
    • Abstract
    • 4.1 Introduction
    • 4.2 Physicochemical Assumptions
    • 4.3 Mathematical Concepts of Simplification in Chemical Kinetics
  • Chapter 5: Physicochemical Devices and Reactors
    • Abstract
    • 5.1 Introduction
    • 5.2 Basic Equations of Diffusion Systems
    • 5.3 Temporal Analysis of Products Reactor: A Basic Reactor-Diffusion System
    • 5.4 TAP Modeling on the Laplace and Time Domain: Theory
    • 5.5 TAP Modeling on the Laplace and Time Domain: Examples
    • 5.6 Multiresponse TAP Theory
    • 5.7 The Y Procedure: Inverse Problem Solving in TAP Reactors
    • 5.8 Two- and Three-Dimensional Modeling
    • 5.9 TAP Variations
    • 5.10 Piecewise Linear Characteristics
    • 5.11 First- and Second-Order Nonideality Corrections in the Modeling of Thin-Zone TAP Reactors
  • Chapter 6: Thermodynamics
    • Abstract
    • 6.1 Introduction
    • 6.2 Chemical Equilibrium and Optimum
    • 6.3 Is It Possible to Overshoot an Equilibrium?
    • 6.4 Equilibrium Relationships for Nonequilibrium Chemical Dependences
    • 6.5 Generalization. Symmetry Relations and Principle of Detailed Balance
    • 6.6 Predicting Kinetic Dependences Based on Symmetry and Balance
    • 6.7 Symmetry Relations for Nonlinear Reactions
    • Appendix
  • Chapter 7: Stability of Chemical Reaction Systems
    • Abstract
    • 7.1 Stability—General concept
    • 7.2 Thermodynamic Lyapunov Functions
    • 7.3 Multiplicity of Steady States in Nonisothermal Systems
    • 7.4 Multiplicity of Steady States in Isothermal Heterogeneous Catalytic Systems
    • 7.5 Chemical Oscillations in Isothermal Systems
    • 7.6 General Procedure for Parametric Analysis
  • Chapter 8: Optimization of Multizone Configurations
    • Abstract
    • 8.1 Reactor Model
    • 8.2 Maximizing the Conversion
    • 8.3 Optimal Positions of Thin Active Zones
    • 8.4 Numerical Experiments in Computing Optimal Active Zone Configurations
    • 8.5 Equidistant Configurations of the Active Zones
  • Chapter 9: Experimental Data Analysis: Data Processing and Regression
    • Abstract
    • 9.1 The Least-Squares Criterion
    • 9.2 The Newton-Gauss Algorithm
    • 9.3 Search Methods From Optimization Theory
    • 9.4 The Levenberg-Marquardt Compromise
    • 9.5 Initial Estimates
    • 9.6 Properties of the Estimating Vector
    • 9.7 Temperature Dependence of the Kinetic Parameters k and Ki
    • 9.8 Genetic Algorithms
  • Chapter 10: Polymers: Design and Production
    • Abstract
    • Acknowledgments
    • 10.1 Introduction
    • 10.2 Microscale Modeling Techniques
    • 10.3 Macroscale Modeling Techniques
    • 10.4 Extension Toward Heterogeneous Polymerization in Dispersed Media
    • 10.5 Extension Toward Heterogeneous Polymerization With Solid Catalysts
    • 10.6 Conclusions
  • Chapter 11: Advanced Theoretical Analysis in Chemical Engineering: Computer Algebra and Symbolic Calculations
    • Abstract
    • 11.1 Critical Simplification
    • 11.2 “Kinetic Dance”: One Step Forward—One Step Back
    • 11.3 Intersections and Coincidences
  • Index


No. of pages:
© Elsevier 2017
eBook ISBN:
Hardcover ISBN:

About the Author

Denis Constales

Denis Constales is an applied mathematician who has been working in chemical engineering and statistics for the past 12 years, specializing in diffusion problems, parameter estimation and inverse problems, chemical kinetics, reaction mechanism identification, and nearly all aspects of the Temporal Analysis of Products method.

Affiliations and Expertise

Department of Mathematics, Ghent University, Belgium

Gregory S. Yablonsky

Gregory Yablonsky has been involved in mathematical modeling of chemical processes, in particular processes of heterogeneous catalysis, for over 30 years. He is an author of more than 200 papers and 6 books on these topics.

Affiliations and Expertise

Parks College of Engineering, Aviation and Technology, St. Louis University, USA

Dagmar D'hooge

Affiliations and Expertise

Department of Chemical Engineering and Technical University at Ghent (Belgium)

Joris W. Thybaut

J W Thybaut holds a PhD in chemical engineering (2002) and is currently associate professor in catalytic reaction engineering. His research activities are centered around fundamental kinetic modeling of complex reactions and the exploitation of these models aiming at rational catalyst design as well as at industrial process enhancement.

Affiliations and Expertise

Department of Chemical Engineering and Technical Chemistry, Ghent University, Belgium

Guy B. Marin

Guy B. Marin

Guy B. Marin is professor in Chemical Reaction Engineering at Ghent University (Belgium) and directs the Laboratory for Chemical Technology. He received his chemical engineering degree from Ghent University in 1976 where he also obtained his Ph.D. in 1980. He previously held a Fulbright fellowship at Stanford University and Catalytica Associates (USA) and was full professor from 1988 to 1997 at Eindhoven University of Technology (The Netherlands) where he taught reactor analysis and design. The investigation of chemical kinetics, aimed at the modeling and design of chemical processes and products all the way from molecule up to full scale, constitutes the core of his research . He wrote a book “Kinetics of Chemical Reactions: Decoding Complexity” with G. Yablonsky (Wiley-VCH, 2011) and co-authored more than 300 papers in international journals. He is editor-in-chief of “Advances in Chemical Engineering”, co-editor of the “Chemical Engineering Journal” and member of the editorial board of “Applied Catalysis A: General” and Industrial & Engineering Chemistry Research”. In 2012 he received an Advanced Grant from the European Research Council (ERC) on “Multiscale Analysis and Design for Process Intensification and Innovation (MADPII)”. He was selected to deliver the 2012 Danckwerts Memorial lecture. He chairs the Working Party on Chemical Reaction Engineering of the European Federation of Chemical Engineering and is “Master” of the 111 project of the Chinese Government for oversees collaborations in this field.

Affiliations and Expertise

Department of Chemical Engineering and Technical Chemistry, Ghent University, Belgium


"I wholeheartedly recommend this book to everyone who works with chemical kinetics or in a related field as it is an enormous resource of useful mathematical techniques. For me, there is something that is even more important than the actual contents. This is the following attitude: quantitative data must be evaluated by quantitative models." --Reaction Kinetics, Mechanisms and Catalysis