Synthesis and Operability Strategies for Computer-Aided Modular Process Intensification

Synthesis and Operability Strategies for Computer-Aided Modular Process Intensification

1st Edition - April 2, 2022

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  • Authors: Efstratios N Pistikopoulos, Yuhe Tian
  • Paperback ISBN: 9780323855877
  • eBook ISBN: 9780323898058

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Synthesis and Operability Strategies for Computer-Aided Modular Process intensification presents state-of-the-art methodological developments and real-world applications for computer-aided process modeling, optimization and control, with a particular interest on process intensification systems. Each chapter consists of basic principles, model formulation, solution algorithm, and step-by-step implementation guidance on key procedures. Sections cover an overview on the current status of process intensification technologies, including challenges and opportunities, detail process synthesis, design and optimization, the operation of intensified processes under uncertainty, and the integration of design, operability and control. Advanced operability analysis, inherent safety analysis, and model-based control strategies developed in the community of process systems engineering are also introduced to assess process operational performance at the early design stage.

Key Features

  • Includes a survey of recent advances in modeling, optimization and control of process intensification systems
  • Presents a modular synthesis approach for process design, integration and material selection in intensified process systems
  • Provides advanced process operability, inherent safety tactics, and model-based control analysis approaches for the evaluation of process operational performance at the conceptual design stage
  • Highlights a systematic framework for multiscale process design intensification integrated with operability and control
  • Includes real-word application examples on intensified reaction and/or separation systems with targeted cost, energy and sustainability improvements


Researchers and Academics in chemical engineering and energy engineering Graduate students with research topics on process systems engineering, process intensification, etc. Undergraduate students in chemical engineering. Industry professionals working on process intensification technologies, process design and modelling, process control, etc.

Table of Contents

  • Cover image
  • Title page
  • Table of Contents
  • Copyright
  • Dedication
  • Authors' biographies
  • Preface
  • Topic 1: introduction on computer-aided modular process intensification
  • Topic 2: process intensification synthesis via a phenomena-based modular representation approach
  • Topic 3: model-based flexibility, inherent safety, and control analysis for modular process intensification systems
  • Topic 4: a systematic framework for the synthesis of operable process intensification systems
  • Part 1: Preliminaries
  • Part 2: Methodologies
  • Part 3: Case studies
  • Acknowledgments
  • Part 1: Preliminaries
  • 1: Introduction to modular process intensification
  • Abstract
  • 1.1. Introduction
  • 1.2. Definitions and principles of modular process intensification
  • 1.3. Modular process intensification technology showcases
  • References
  • 2: Computer-aided modular process intensification: design, synthesis, and operability
  • Abstract
  • 2.1. Conceptual synthesis and design
  • 2.2. Operability, safety, and control analysis
  • 2.3. Research challenges and key questions
  • References
  • Part 2: Methodologies
  • 3: Phenomena-based synthesis representation for modular process intensification
  • Abstract
  • 3.1. A prelude on phenomena-based PI synthesis
  • 3.2. Generalized Modular Representation Framework
  • 3.3. Driving force constraints
  • 3.4. Key features of GMF synthesis
  • 3.5. Motivating examples
  • References
  • 4: Process synthesis, optimization, and intensification
  • Abstract
  • 4.1. Problem statement
  • 4.2. GMF synthesis model
  • 4.3. Pseudo-capital cost estimation
  • 4.4. Solution strategy
  • 4.5. Motivating example: GMF synthesis representation and optimization of a binary distillation system
  • Nomenclature
  • References
  • 5: Enhanced GMF for process synthesis, intensification, and heat integration
  • Abstract
  • 5.1. GMF synthesis model with Orthogonal Collocation
  • 5.2. GMF synthesis model with heat integration
  • 5.3. Motivating example: GMF synthesis, intensification, and heat integration of a ternary separation system
  • References
  • 6: Steady-state flexibility analysis
  • Abstract
  • 6.1. Basic concepts
  • 6.2. Problem definition
  • 6.3. Solution algorithms
  • 6.4. Design and synthesis of flexible processes
  • 6.5. Tutorial example: flexibility analysis of heat exchanger network
  • References
  • 7: Inherent safety analysis
  • Abstract
  • 7.1. Dow Chemical Exposure Index
  • 7.2. Dow Fire and Explosion Index
  • 7.3. Safety Weighted Hazard Index
  • 7.4. Quantitative risk assessment
  • References
  • 8: Multi-parametric model predictive control
  • Abstract
  • 8.1. Process control basics
  • 8.2. Explicit model predictive control via multi-parametric programming
  • 8.3. The PAROC framework
  • 8.4. Case study: multi-parametric model predictive control of an extractive distillation column
  • References
  • 9: Synthesis of operable process intensification systems
  • Abstract
  • 9.1. Problem statement
  • 9.2. A systematic framework for synthesis of operable process intensification systems
  • 9.3. Steady-state synthesis with flexibility and safety considerations
  • 9.4. Motivating example: heat exchanger network synthesis
  • References
  • Part 3: Case studies
  • 10: Envelope of design solutions for intensified reaction/separation systems
  • Abstract
  • 10.1. The Feinberg Decomposition
  • 10.2. Case study: olefin metathesis
  • References
  • 11: Process intensification synthesis of extractive separation systems with material selection
  • Abstract
  • 11.1. Problem statement
  • 11.2. Case study: ethanol-water separation
  • References
  • 12: Process intensification synthesis of dividing wall column systems
  • Abstract
  • 12.1. Case study: methyl methacrylate purification
  • 12.2. Base case design and simulation analysis
  • 12.3. Process intensification synthesis via GMF
  • References
  • 13: Operability and control analysis in modular process intensification systems
  • Abstract
  • 13.1. Loss of degrees of freedom
  • 13.2. Role of process constraints
  • 13.3. Numbering up vs. scaling up
  • 13.4. Remarks
  • References
  • 14: A framework for synthesis of operable and intensified reactive separation systems
  • Abstract
  • 14.1. Process description
  • 14.2. Synthesis of intensified and operable MTBE production systems
  • References
  • 15: A software prototype for synthesis of operable process intensification systems
  • Abstract
  • 15.1. The SYNOPSIS software prototype
  • 15.2. Case study: pentene metathesis reaction
  • References
  • A: Process modeling, synthesis, and control of reactive distillation systems
  • A.1. Modeling of reactive distillation systems
  • A.2. Short-cut design of reactive distillation
  • A.3. Synthesis design of reactive distillation
  • A.4. Process control of reactive distillation
  • A.5. Software tools for modeling, simulation, and design of reactive distillation
  • References
  • B: Driving force constraints and physical and/or chemical equilibrium conditions
  • B.1. Pure separation systems
  • B.2. Reactive separation systems
  • B.3. Pure reaction systems
  • C: Reactive distillation dynamic modeling
  • C.1. Process structure
  • C.2. Tray modeling
  • C.3. Reboiler and condenser modeling
  • C.4. Physical properties
  • C.5. Initial conditions
  • C.6. Equipment cost correlations
  • References
  • D: Nonlinear optimization formulation of the Feinberg Decomposition approach
  • References
  • E: Degrees of freedom analysis and controller design in modular process intensification systems
  • E.1. Degrees of freedom analysis
  • E.2. Controller tuning for olefin metathesis case study
  • References
  • F: MTBE reactive distillation model validation and dynamic analysis
  • F.1. MTBE reactive distillation model validation with commercial Aspen simulator
  • F.2. Steady-state and dynamic analyses on the selection of manipulated variable for MTBE reactive distillation
  • References
  • Index

Product details

  • No. of pages: 336
  • Language: English
  • Copyright: © Elsevier 2022
  • Published: April 2, 2022
  • Imprint: Elsevier
  • Paperback ISBN: 9780323855877
  • eBook ISBN: 9780323898058

About the Authors

Efstratios N Pistikopoulos

Professor Efstratios N. Pistikopoulos is the Director of the Texas A&M Energy Institute and the Dow Chemical Chair Professor in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. He was a Professor of Chemical Engineering at Imperial College London, UK (1991-2015) and the Director of its Centre for Process Systems Engineering (2002-2009). He holds a Ph.D. degree from Carnegie Mellon University and he worked with Shell Chemicals in Amsterdam before joining Imperial. He has authored or co-authored over 500 major research publications in the areas of modelling, control and optimization of process, energy and systems engineering applications, 15 books and 3 patents. He is a Fellow of IChemE and AIChE, and the Editor-in-Chief of Computers & Chemical Engineering. In 2007, Prof. Pistikopoulos was a co-recipient of the prestigious MacRobert Award from the Royal Academy of Engineering. In 2012, he was the recipient of the Computing in Chemical Engineering Award of CAST/AIChE, while in 2020 he received the Sargent Medal from the Institution of Chemical Engineers (IChemE). He is a member of the Academy of Medicine, Engineering and Science of Texas. In 2021, he received the AIChE Sustainable Engineering Forum Research Award. He received the title of Doctor Honoris Causa in 2014 from the University Politehnica of Bucharest, and from the University of Pannonia in 2015. In 2013, he was elected Fellow of the Royal Academy of Engineering in the United Kingdom.

Affiliations and Expertise

Texas A&M Energy Institute, Texas A&M University, College Station, Texas, United States Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas, United States

Yuhe Tian

Dr. Yuhe Tian is Assistant Professor in the Department of Chemical and Biomedical Engineering at West Virginia University. Prior to joining WVU, she received her Ph.D. degree in Chemical Engineering from Texas A&M University under the supervision of Prof. Efstratios N. Pistikopoulos (2016-2021). She holds Bachelor’s degrees in Chemical Engineering and Applied Mathematics from Tsinghua University, China (2012-2016). Her research focuses on the development and application of multi-scale systems engineering tools for modular process intensification, clean energy innovation, systems integration, and sustainable supply chain optimization.

Affiliations and Expertise

Department of Chemical and Biomedical Engineering, West Virginia University, Morgantown, West Virginia, United States

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