Simulation and Optimization in Process Engineering

The Benefit of Mathematical Methods in Applications of the Chemical Industry

Michael Bortz, Norbert Asprion

• Publisher: Elsevier
• Year: 2022
• Print ISBN:
  9780323850438
• eBook ISBN:
  9780323850445
• Topic: Technology & Engineering
• Subtopic: Chemical & Biochemical Engineering
• Index: Technology & Engineering

Simulation and Optimization in Process Engineering: The Benefit of Mathematical Methods in Applications of the Process Industry brings together examples where the successful transfer of progress made in mathematical simulation and optimization has led to innovations in an industrial context that created substantial benefit. Containing introductory accounts on scientific progress in the most relevant topics of process engineering (substance properties, simulation, optimization, optimal control and real time optimization), the examples included illustrate how such scientific progress has been transferred to innovations that delivered a measurable impact, covering details of the methods used, and more. With each chapter bringing together expertise from academia and industry, this book is the first of its kind, providing demonstratable insights. - Recent mathematical methods are transformed into industrially relevant innovations. - Covers recent progress in mathematical simulation and optimization in a process engineering context with chapters written by experts from both academia and industry - Provides insight into challenges in industry aiming for a digitized world.

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• Preface
• List of Illustrations
• List of Tables
• Chapter 1: Prediction and correlation of physical properties including transport and interfacial properties with the PC-SAFT equation of state
• Chapter 2: Don’t search—Solve! Process optimization modeling with IDAES
• Chapter 3: Thinking multicriteria—A jackknife when it comes to optimization
• Chapter 4: Integrated modeling and energetic optimization of the steelmaking process in electric arc furnaces: An industrial application
• Chapter 5: Solvent recovery by batch distillation—Application of multivariate sensitivity studies to high dimensional multiobjective optimization problems
• Chapter 6: Modeling and optimizing dynamic networks: Applications in process engineering and energy supply
• Chapter 7: The use of digital twins to overcome low-redundancy problems in process data reconciliation
• Chapter 8: Real-time optimization of batch processes via optimizing feedback control
• Chapter 9: On economic operation of switchable chlor-alkali electrolysis for demand-side management
• Chapter 10: Optimal experiment design for dynamic processes
• Chapter 11: Characterization of reactions and growth in automated continuous flow and bioreactor platforms—From linear DoE to model-based approaches
• Chapter 12: Product development in a multicriteria context
• Chapter 13: Dispatching for batch chemical processes using Monte-Carlo simulations—A practical approach to scheduling in operations
• Chapter 14: Applications of the RTN scheduling model in the chemical industry
• Index