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Dynamic process modeling / edited by Michael C. Georgiadis, Julio R. Banga, and Efstratios N. Pistikopoulos. — Weinheim : Wiley-VCH ; [Chichester : John Wiley, distributor], c2011. – (81.1031/D997) |
Contents
Contents
Preface xv
List of Contributors
Part I Chemical and Other Processing Systems
1 Dynamic Process Modeling: Combining Models and Experimenta Data to Solve Industrial Problems 3
1.1 Introduction 3
1.2 Dynamic Process Modeling - Background and Basics 5
1.3 A Model-Based Engineering Approach 14
1.4 An Example: Multitubular Reactor Design 23
1.5 Conclusions 31
2 Dynamic Multiscale Modeling - An Application to Granulation Processes 35
2.1 Introduction 35
2.2 Granulation 36
2.3 Multiscale Modeling of Process Systems 41
2.4 Scales of Interest in Granulation 45
2.5 Applications of Dynamic Multiscale Modeling to Granulation
2.6 Conclusions 61
3 Modeling of Polymerization Processes 67
3.1 Introduction 67
3.2 Free-Radical Homopolymerization 68
3.3 Free-Radical Multicomponent Polymerization 77
3.4 Modeling of Polymer Molecular Properties 80
3.5 A Practical Approach - SAN Bulk Polymerization 90
3.6 Conclusions 97
4 Modeling and Control of Proton Exchange Membrane Fuel Cells 105
4.1 Introduction 105
4.2 Literature Review 108
4.3 Motivation 109
4.4 PEM Fuel Cell Mathematical Model 113
4.5 Reduced Order Model 128
4.6 Concluding Remarks 132
5 Modeling of Pressure Swing Adsorption Processes 137
5.1 Introduction 137
5.2 Model Formulation 144
5.3 Case-Study Applications 163
5.4 Conclusions 167
6 A Framework for the Modeling of Reactive Separations 173
6.1 Introduction 173
6.2 Reactive Separations 174
6.3 Classification of Modeling Methods 176
6.4 Fluid-Dynamic Approach 178
6.5 Hydrodynamic Analogy Approach 183
6.6 Rate-Based Approach 188
6.7 Parameter Estimation and Virtual Experiments 193
6.8 Benefits of the Complementary Modeling 196
6.9 Concluding Remarks 199
7 Efficient Reduced Order Dynamic Modeling of Complex Reactive and Multiphase Separation Processes Using Orthogonal Collocation on Finite Elements 203
7.1 Introduction 203
7.2 NEQ/OCFE Model Formulation 205
7.3 Adaptive NEQ/OCFE for Enhanced Performance 218
7.4 Dynamic Simulation Results 220
7.5 Epilog 234
8 Modeling of Crystallization Processes 239
8.1 Introduction 239
8.2 Background 240
8.3 Solubility Predictions 243
8.4 Crystallization Mechanisms 251
8.5 Population， Mass， and Energy Balances 256
8.6 Crystal Characterization 264
8.7 Solution Environment and Model Application 266
8.8 Optimization 270
8.9 Future Outlook 276
9 Modeling Multistage Flash Desalination Process - Current Status and Future Development 287
9.1 Introduction 287
9.2 Issues in MSF Desalination Process 289
9.3 State-of-the-Art in Steady-State Modeling of M S F Desalination Process 292
9.4 State-of-the-Art in Dynamic Modeling of M S F Desalination Process 303
9.5 Case Study 308
9.6 Future Challenges 312
9.7 Conclusions 315
Part II Biological， Bio-Processing and Biomedical Systems 319
10 Dynamic Models of Disease Progression: Toward a Multiscale Model of Systemic Inflammation in Humans 321
10.1 Introduction 321
10.2 Background 322
10.3 Methods 328
10.4 Results 340
10.5 Conclusions 360
11 Dynamic Modeling and Simulation for Robust Control of Distributed Processes and Bioprocesses 369
11.1 Introduction 369
11.2 Model Reduction of DPS: Theoretical Background 372
11.3 Model Reduction in Identification of Bioprocesses 377
11.4 Model Reduction in Control Applications 383
11.5 Conclusions 397
12 Model Development and Analysis of Mammalian Cell Culture Systems 403
12.1 Introduction 403
12.2 Review of Mathematical Models of Mammalian Cell Culture Systems 406
12.3 Motivation 410
12.4 Dynamic Modeling of Biological Systems - An Illustrative Example 413
12.5 Concluding Remarks 435
13 Dynamic Model Building Using Optimal Identification Strategies， with Applications in Bioprocess Engineering 441
13.1 Introduction 441
13.2 Parameter Estimation: Problem Formulation 443
13.3 Identifiability 447
13.4 Optimal Experimental Design 449
13.5 Nonlinear Programming Solvers 450
13.6 Illustrative Examples 453
13.7 Overview 463
14 Multiscale Modeling of Transport Phenomena in Plant-Based Foods 469
14.1 Introduction 469
14.2 Length Scales of Biological Materials 470
14.3 Multiscale Modeling of Transport Phenomena 472
14.4 Numerical Solution 476
14.5 Case Study: Application of Multiscale Gas Exchange in Fruit 480
14.6 Conclusions and Outlook 485
15 Synthetic Biology: Dynamic Modeling and Construction of Cell Systems 493
15.1 Introduction 493
15.2 Constructing a Model with Parts 494
15.3 Modeling Regimes and Simulation Techniques 518
15.4 Application 532
15.5 Conclusions 541
16 Identification of Physiological Models of Type 1 Diabetes Mellitus by Model-Based Design of Experiments 545
16.1 Introduction 546
16.2 Introducing Physiological Models
16.3 Identifying a Physiological Model Design 548
16.4 Standard Clinical Tests 550
16.5 A Compartmental Model of Glucose Homeostasis 551
16.6 Model Identifiability Issues 552
16.7 Design of Experiments Under Constraints for Physiological Models 556
16.8 Design of Experimental Protocols 560
16.9 Dealing with Uncertainty 563
16.10 Conclusions 572
Index 583
