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Simulation and Optimization in Process Engineering
The Benefit of Mathematical Methods in Applications of the Chemical Industry
1st Edition - April 16, 2022
Editors: Michael Bortz, Norbert Asprion
Language: English
Paperback ISBN:9780323850438
9 7 8 - 0 - 3 2 3 - 8 5 0 4 3 - 8
eBook ISBN:9780323850445
9 7 8 - 0 - 3 2 3 - 8 5 0 4 4 - 5
Simulation and Optimization in Process Engineering: The Benefit of Mathematical Methods in Applications of the Process Industry brings together examples where the successfu…Read more
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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.
Chemical engineers, process engineers, research and development staff in the process industry. Mathematicians, physicists, computer scientists
Cover image
Title page
Table of Contents
Copyright
Contributors
Preface
Chapter 1: Prediction and correlation of physical properties including transport and interfacial properties with the PC-SAFT equation of state
Abstract
1: Model equations of PC-SAFT
2: Parameterization
3: Group-contribution methods for PC-SAFT
4: Transport properties
5: Interfacial properties
References
Chapter 2: Don’t search—Solve! Process optimization modeling with IDAES
Abstract
1: Introduction
2: Solution algorithms and optimization models
3: Advanced optimization for differential-algebraic applications
4: The IDAES optimization modeling software platform
5: Carbon capture optimization case study
6: Conclusions and future perspectives
References
Chapter 3: Thinking multicriteria—A jackknife when it comes to optimization
Abstract
Acknowledgments
1: Introduction
2: Process design
3: Model adjustment, model comparison and model-based design of experiments
4: Decision support
References
Chapter 4: Integrated modeling and energetic optimization of the steelmaking process in electric arc furnaces: An industrial application
Abstract
1: Introduction
2: Electric arc furnace process model
3: Dynamic optimization of the melting profiles
4: Solution using control vector parametrization
5: Results and discussions
6: Conclusions
References
Chapter 5: Solvent recovery by batch distillation—Application of multivariate sensitivity studies to high dimensional multiobjective optimization problems
Abstract
1: Introduction
2: Problem definition
3: Literature review
4: Methodology
5: Set up of the flowsheet simulation
6: Results
7: Summary
References
Chapter 6: Modeling and optimizing dynamic networks: Applications in process engineering and energy supply
Abstract
Acknowledgment
1: Introduction
2: AD-Net
3: Applications in energy supply
4: Applications in batch distillation
5: Conclusion
References
Chapter 7: The use of digital twins to overcome low-redundancy problems in process data reconciliation
Abstract
Acknowledgments
1: Introduction
2: Data reconciliation
3: Clever mean and clever variance (cm and cv)
4: Median and mad
5: Industrial case study: Itelyum Regeneration amine washing unit
6: Results
7: Conclusions
References
Chapter 8: Real-time optimization of batch processes via optimizing feedback control
Abstract
1: Introduction
2: Representation of batch processes
3: Numerical optimization of batch processes
4: Feedback-based optimization of uncertain batchprocesses
Chapter 9: On economic operation of switchable chlor-alkali electrolysis for demand-side management
Abstract
Acknowledgments
1: Introduction
2: Operational mode switching of chlor-alkali electrolysis
3: Mathematical formulation for optimal sizing and operation of switchable chlor-alkali electrolysis
4: Case study
5: Conclusion
References
Chapter 10: Optimal experiment design for dynamic processes
Abstract
1: Introduction
2: Optimal experiment design for model structure discrimination
3: Optimal experiment design for parameter estimation
4: Advanced developments in optimal experiment design
5: Conclusions
References
Chapter 11: Characterization of reactions and growth in automated continuous flow and bioreactor platforms—From linear DoE to model-based approaches
Abstract
1: Introduction
2: Miniaturized platforms and applications
3: Special aspects and challenges
4: Industry view
5: Discussion and conclusions
References
Chapter 12: Product development in a multicriteria context
Abstract
1: Introduction
2: Model fitting
3: Multicriteria optimization and decision-making
4: Approximating the set of efficient product designs
5: Navigating the set of efficient product designs
6: The role of Qritos in the design process
7: Application: Designing an exterior paint recipe
8: Outlook
References
Chapter 13: Dispatching for batch chemical processes using Monte-Carlo simulations—A practical approach to scheduling in operations
Abstract
1: Introduction
2: Proposed solution
3: Implementation
4: Beyond real-time operative scheduling
5: Conclusions and outlook
References
Chapter 14: Applications of the RTN scheduling model in the chemical industry
Abstract
Acknowledgments
1: Introduction
2: Review of RTN model
3: Industry-led developments
4: Industrial impact
5: Conclusions
References
Index
No. of pages: 428
Language: English
Edition: 1
Published: April 16, 2022
Imprint: Elsevier
Paperback ISBN: 9780323850438
eBook ISBN: 9780323850445
MB
Michael Bortz
Michael Bortz studied Physics in Dortmund and Grenoble. He received his Ph.D. in many particle physics at Dortmund University in 2003. After that, he worked as a PostDoc at universities in Wuppertal, Canberra (Australian National University), Oxford, and Kaiserslautern. In 2009 he joined the Fraunhofer Institute for Industrial Mathematics in Kaiserslautern, where he is now leading the department for optimization of technical processes. His research interests are in modeling, simulating, and optimizing processes in different application domains, including medical therapy planning, mechanical, and chemical engineering. He has realized numerous projects with cooperation partners from the chemical industry, leveraging the benefit of interactive decision support. Since 2021, he is associate professor at the Technical University Kaiserslautern.
Affiliations and expertise
Head of Department, Fraunhofer Institute for Industrial Mathematics, Kaiserslautern, Germany and Associate Professor, Technical University, Kaiserslautern, Germany.
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Norbert Asprion
Norbert Asprion studied mechanical engineering at University of Kaiserslautern, Germany and received his Ph.D. (Supervisor Prof. G. Maurer) in the field of thermodynamics of hydrogen-bonding solutions from Kaiserslautern University in 1996. Since then, he has been with BASF SE in Ludwigshafen. After several positions in process development and six years in technical marketing, he is now product manager for “Computational Engineering Solutions” in the department “Digitalization in Research & Development.” His research interest is focused on process modeling, simulation, and optimization to support decision making in process development. He is a Research Fellow at BASF, a member of the EFCE CAPE working party and the COLaN management board.
Affiliations and expertise
Research Fellow, BASF SE, Ludwigshafen, Ludwigshafen am Rhein, Germany
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