Simulation and Optimization in Process Engineering: The Benefit of Mathematical Methods in Applications of the Chemical Industry
Editat de Michael Bortz, Norbert Asprionen Limba Engleză Paperback – 21 apr 2022
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.
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Specificații
ISBN-13: 9780323850438
ISBN-10: 032385043X
Pagini: 428
Dimensiuni: 152 x 229 mm
Greutate: 0.57 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 032385043X
Pagini: 428
Dimensiuni: 152 x 229 mm
Greutate: 0.57 kg
Editura: ELSEVIER SCIENCE
Public țintă
Chemical engineers, process engineers, research and development staff in the process industryCuprins
1. The PC-SAFT Equation of State
2. Don't Search - Solve! Process Optimization Modeling with IDAES
3. Thinking Multicriteria - A Jackknife When it Comes to Optimization
4. Dynamic modelling, simulation, optimization
5. Solvent Recovery by Batch Distillation - Application of Multivariate Sensitivity Studies to High Dimensional Multi-Objective Optimization Problems
6. Modeling and Optimizing Dynamic Networks: Applications in Process Engineering and Energy Supply
7. The Use of Digital Twins to Overcome Low-redundancy Problems in Process Data Reconciliation
8. Real-Time Optimization of Batch Chemical Processes – Combining within-batch and batch-to-batch corrections
9. On economic operation of switchable chlor-alkali electrolysis for demand side management
10. Optimal experimental design for dynamical processes
11. Characterization of reactions and growth in automated continuous flow and bioreactor platforms – From linear DoE to model-based approaches
12. Product development in a multicriteria context
13. Dispatching for batch chemical processes using Monte-Carlo simulations -- a practical approach to scheduling on the shop floor
14. Applications of the RTN Scheduling Model in the Chemical Industry
2. Don't Search - Solve! Process Optimization Modeling with IDAES
3. Thinking Multicriteria - A Jackknife When it Comes to Optimization
4. Dynamic modelling, simulation, optimization
5. Solvent Recovery by Batch Distillation - Application of Multivariate Sensitivity Studies to High Dimensional Multi-Objective Optimization Problems
6. Modeling and Optimizing Dynamic Networks: Applications in Process Engineering and Energy Supply
7. The Use of Digital Twins to Overcome Low-redundancy Problems in Process Data Reconciliation
8. Real-Time Optimization of Batch Chemical Processes – Combining within-batch and batch-to-batch corrections
9. On economic operation of switchable chlor-alkali electrolysis for demand side management
10. Optimal experimental design for dynamical processes
11. Characterization of reactions and growth in automated continuous flow and bioreactor platforms – From linear DoE to model-based approaches
12. Product development in a multicriteria context
13. Dispatching for batch chemical processes using Monte-Carlo simulations -- a practical approach to scheduling on the shop floor
14. Applications of the RTN Scheduling Model in the Chemical Industry