CRC Press
219 pages | 95 B/W Illus.
This title introduces the underlying theory and demonstrates practical applications in different process industries using hybrid modeling.
It reviews hybrid modeling approach applicability in wide range of process industries, recommends how to increase hybrid model performance and throw Insights into cost efficient practices in modeling techniques
Discusses advance process operation maximizing the benefits of available process knowledge and Includes real-life and practical case studies
Chapter 1: Benefits and challenges of hybrid modelling in the process industries: An introduction
Moritz von Stosch, Jarka Glassey
1.1 An intuitive introduction to hybrid modelling
1.2 Key-properties and challenges of hybrid modelling
1.3 Benefits and challenges of hybrid modelling in the process industries
1.4 Hybrid modelling, the idea and its history
1.5 Setting the stage
Chapter 2: Hybrid Model Structures for Knowledge Integration
Moritz von Stosch, Rui M.C. Portela, Rui Oliveira
2.1. Introduction
2.2. Hybrid semi-parametric model structures
2.3. Examples
2.4. Concluding remarks
Chapter 3: Hybrid models and Experimental Design
Moritz von Stosch
3.1. Introduction
3.2. Design of Experiments (DoE)
3.3. The Validity/Applicability Domain of hybrid models
3.4. Hybrid model based (Optimal) Experimental Design
3.5. Conclusions
Chapter 4: Hybrid model identification and discrimination with practical examples from the chemical industry
Schuppert and Th. Mrziglod
4.1 Introduction
4.2 Why data based modelling?
4.3 Principles of data based modelling
4.4 Structured hybrid modelling – introduction
4.5. Practical realisation of Hybrid Models
4.6 Applications
4.7. Summary
Chapter 5: Hybrid modeling of biochemical processes
Vytautas Galvanauskas and Rimvydas Simutis, Andreas Lübbert
5.1 Introduction
5.2 Hybrid modeling for process optimization
5.3 Hybrid modeling for state estimation
5.4 Hybrid modeling for control
5.5 Hybrid modeling for fault analysis
5.6 Concluding remarks
Chapter 6: Hybrid modelling of petrochemical processes
Vladimir Mahalec
6.1 Introduction
6.2 Computation of mass and energy balances
6.3 Hybrid Models of petrochemical reactors
6.4 Hybrid Models of Simple Distillation Towers
6.5 Hybrid Models of Complex Distillation Towers
6.6 Summary
Chapter 7: Implementation of hybrid neural models to predict the behaviour of food transformation and food waste valorisation processes
Stefano Curcio
7.1 Introduction
7.2 Case study 1 – Convective drying of vegetables
7.3. Case study 2 – Enzymatic transesterification of waste olive oil glycerides for biodiesel production
7.4 Conclusions
Chapter 8: Hybrid modelling of pharmaceutical processes and PAT
Jarka Glassey
8.1 Quality by Design and Process Analytical Technologies
8.2 Case study
8.3 Conclusions
