Item Details

Process Modelling and Model Analysis

K.M. Hangos, I. T. Cameron
Format
Book
Published
San Diego : Academic Press, c2001.
Language
English
Series
Process Systems Engineering
ISBN
0121569314
Contents
  • I Fundamental Principles and Process Model Development
  • 1 Role of Models in Process Systems Engineering
  • 1.1. Idea of a Model 4
  • 1.2. Model Application Areas in PSE 7
  • 1.3. Model Classification 10
  • 1.4. Model Characteristics 12
  • 1.5. A Brief Historical Review of Modelling in PSE 13
  • 2 A Systematic Approach to Model Building
  • 2.1. Process System and the Modelling Goal 20
  • 2.2. Mathematical Models 22
  • 2.3. A Systematic Modelling Procedure 24
  • 2.4. Ingredients of Process Models 32
  • 3 Conservation Principles
  • 3.1. Thermodynamic Principles of Process Systems 42
  • 3.2. Principle of Conservation 51
  • 3.3. Balance Volumes in Process System Applications 58
  • 4 Constitutive Relations
  • 4.1. Transfer Rate Equations 65
  • 4.2. Reaction Kinetics 70
  • 4.3. Thermodynamical Relations 72
  • 4.4. Balance Volume Relations 75
  • 4.5. Equipment and Control Relations 75
  • 5 Dynamic Models--Lumped Parameter Systems
  • 5.1. Characterizing Models and Model Equation Sets 83
  • 5.2. Lumped Parameter Models--Initial Value Problems (IVPs) 84
  • 5.3. Conservation Balances for Mass 86
  • 5.4. Conservation Balances for Energy 89
  • 5.5. Conservation Balances for Momentum 95
  • 5.6. Set of Conservation Balances for Lumped Systems 98
  • 5.7. Conservation Balances in Intensive Variable Form 99
  • 5.8. Dimensionless Variables 101
  • 5.9. Normalization of Balance Equations 102
  • 5.10. Steady-State Lumped Parameter Systems 103
  • 5.11. Analysis of Lumped Parameter Models 104
  • 5.12. Stability of the Mathematical Problem 114
  • 6 Solution Strategies for Lumped Parameter Models
  • 6.1. Process Engineering Example Problems 124
  • 6.2. Ordinary Differential Equations 125
  • 6.3. Basic Concepts in Numerical Methods 126
  • 6.4. Local Truncation Error and Stability 129
  • 6.5. Stability of the Numerical Method 133
  • 6.6. Key Numerical Methods 137
  • 6.7. Differential-Algebraic Equation Solution Techniques 149
  • 7 Dynamic Models--Distributed Parameter Systems
  • 7.1. Development of DPS Models 163
  • 7.2. Examples of Distributed Parameter Modelling 174
  • 7.3. Classification of DPS Models 182
  • 7.4. Lumped Parameter Models for Representing DPSs 185
  • 8 Solution Strategies for Distributed Parameter Models
  • 8.1. Areas of Interest 191
  • 8.2. Finite Difference Methods 192
  • 8.3. Method of Lines 201
  • 8.4. Method of Weighted Residuals 203
  • 8.5. Orthogonal Collocation 206
  • 8.6. Orthogonal Collocation for Partial Differential Equations 216
  • 9 Process Model Hierarchies
  • 9.1. Hierarchy Driven by the Level of Detail 225
  • 9.2. Hierarchy Driven by Characteristic Sizes 233
  • 9.3. Hierarchy Driven by Characteristic Times 239
  • II Advanced Process Modelling and Model Analysis
  • 10 Basic Tools for Process Model Analysis
  • 10.1. Problem Statements and Solutions 251
  • 10.2. Basic Notions in Systems and Control Theory 253
  • 10.3. Lumped Dynamic Models as Dynamic System Models 264
  • 10.4. State Space Models and Model Linearization 269
  • 10.5. Structural Graphs of Lumped Dynamic Models 277
  • 11 Data Acquisition and Analysis
  • 11.1. Sampling of Continuous Time Dynamic Models 286
  • 11.2. Data Screening 289
  • 11.3. Experiment Design for Parameter Estimation of Static Models 294
  • 11.4. Experiment Design for Parameter Estimation of Dynamic Models 295
  • 12 Statistical Model Calibration and Validation
  • 12.1. Grey-Box Models and Model Calibration 300
  • 12.2. Model Parameter and Structure Estimation 302
  • 12.3. Model Parameter Estimation for Static Models 314
  • 12.4. Identification: Model Parameter and Structure Estimation of Dynamic Models 318
  • 12.5. CSTR: A Case Study of Model Parameter Estimation 323
  • 12.6. Statistical Model Validation via Parameter Estimation 330
  • 13 Analysis of Dynamic Process Models
  • 13.1. Analysis of Basic Dynamical Properties 336
  • 13.2. Analysis of Structural Dynamical Properties 341
  • 13.3. Model Simplification and Reduction 350
  • 14 Process Modelling for Control and Diagnostic Purposes
  • 14.1. Model-Based Process Control 364
  • 14.2. Model-Based Process Diagnosis 370
  • 14.3. Qualitative, Logical and AI Models 372
  • 15 Modelling Discrete Event Systems
  • 15.1. Characteristics and Issues 388
  • 15.2. Approaches to Model Representation 388
  • 15.3. Solution of Discrete Event Dynamic System Models 404
  • 15.4. Analysis of Discrete Event Systems 408
  • 16 Modelling Hybrid Systems
  • 16.1. Hybrid Systems Basics 415
  • 16.2. Approaches to Model Representation 420
  • 16.3. Analysis of Hybrid Systems 430
  • 16.4. Solution of Hybrid System Models 431
  • 17 Modelling Applications in Process Systems
  • 17.1. Copper Converter Dynamics 438
  • 17.2. Destruction of Phenol in Wastewater by Photochemical Reaction 445
  • 17.3. Prefermenter System for Wastewater Treatment 451
  • 17.4. Granulation Circuit Modelling 456
  • 17.5. Industrial Depropanizer using Structural Packing 462
  • 18 Computer Aided Process Modelling
  • 18.2. Industrial Demands on Computer Aided Modelling Tools 472
  • 18.3. Basic Issues in CAPM Tools 474
  • 18.4. Approaches to CAPM Tool Development 483
  • 19 Empirical Model Building
  • 19.2. Modelling Procedure Revisited 494
  • 19.3. Black-Box Modelling 497
  • 19.4. Traps and Pitfalls in Empirical Model Building 511
  • Appendix Basic Mathematic Tools 517
  • A.1. Random Variables and Their Properties 517
  • A.2. Hypothesis Testing 521
  • A.3. Vector and Signal Norms 522
  • A.4. Matrix and Operator Norms 523
  • A.5. Graphs 524.
Description
xvi, 543 p. : ill. ; 26 cm.
Notes
Includes bibliographical references and index.
Series Statement
Process systems engineering ; v. 4
Technical Details
  • Access in Virgo Classic

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    g| I t| Fundamental Principles and Process Model Development -- g| 1 t| Role of Models in Process Systems Engineering -- g| 1.1. t| Idea of a Model g| 4 -- g| 1.2. t| Model Application Areas in PSE g| 7 -- g| 1.3. t| Model Classification g| 10 -- g| 1.4. t| Model Characteristics g| 12 -- g| 1.5. t| A Brief Historical Review of Modelling in PSE g| 13 -- g| 2 t| A Systematic Approach to Model Building -- g| 2.1. t| Process System and the Modelling Goal g| 20 -- g| 2.2. t| Mathematical Models g| 22 -- g| 2.3. t| A Systematic Modelling Procedure g| 24 -- g| 2.4. t| Ingredients of Process Models g| 32 -- g| 3 t| Conservation Principles -- g| 3.1. t| Thermodynamic Principles of Process Systems g| 42 -- g| 3.2. t| Principle of Conservation g| 51 -- g| 3.3. t| Balance Volumes in Process System Applications g| 58 -- g| 4 t| Constitutive Relations -- g| 4.1. t| Transfer Rate Equations g| 65 -- g| 4.2. t| Reaction Kinetics g| 70 -- g| 4.3. t| Thermodynamical Relations g| 72 -- g| 4.4. t| Balance Volume Relations g| 75 -- g| 4.5. t| Equipment and Control Relations g| 75 -- g| 5 t| Dynamic Models--Lumped Parameter Systems -- g| 5.1. t| Characterizing Models and Model Equation Sets g| 83 -- g| 5.2. t| Lumped Parameter Models--Initial Value Problems (IVPs) g| 84 -- g| 5.3. t| Conservation Balances for Mass g| 86 -- g| 5.4. t| Conservation Balances for Energy g| 89 -- g| 5.5. t| Conservation Balances for Momentum g| 95 -- g| 5.6. t| Set of Conservation Balances for Lumped Systems g| 98 -- g| 5.7. t| Conservation Balances in Intensive Variable Form g| 99 -- g| 5.8. t| Dimensionless Variables g| 101 -- g| 5.9. t| Normalization of Balance Equations g| 102 -- g| 5.10. t| Steady-State Lumped Parameter Systems g| 103 -- g| 5.11. t| Analysis of Lumped Parameter Models g| 104 -- g| 5.12. t| Stability of the Mathematical Problem g| 114 -- g| 6 t| Solution Strategies for Lumped Parameter Models -- g| 6.1. t| Process Engineering Example Problems g| 124 -- g| 6.2. t| Ordinary Differential Equations g| 125 -- g| 6.3. t| Basic Concepts in Numerical Methods g| 126 -- g| 6.4. t| Local Truncation Error and Stability g| 129 -- g| 6.5. t| Stability of the Numerical Method g| 133 -- g| 6.6. t| Key Numerical Methods g| 137 -- g| 6.7. t| Differential-Algebraic Equation Solution Techniques g| 149 -- g| 7 t| Dynamic Models--Distributed Parameter Systems -- g| 7.1. t| Development of DPS Models g| 163 -- g| 7.2. t| Examples of Distributed Parameter Modelling g| 174 -- g| 7.3. t| Classification of DPS Models g| 182 -- g| 7.4. t| Lumped Parameter Models for Representing DPSs g| 185 -- g| 8 t| Solution Strategies for Distributed Parameter Models -- g| 8.1. t| Areas of Interest g| 191 -- g| 8.2. t| Finite Difference Methods g| 192 -- g| 8.3. t| Method of Lines g| 201 -- g| 8.4. t| Method of Weighted Residuals g| 203 -- g| 8.5. t| Orthogonal Collocation g| 206 -- g| 8.6. t| Orthogonal Collocation for Partial Differential Equations g| 216 -- g| 9 t| Process Model Hierarchies -- g| 9.1. t| Hierarchy Driven by the Level of Detail g| 225 -- g| 9.2. t| Hierarchy Driven by Characteristic Sizes g| 233 -- g| 9.3. t| Hierarchy Driven by Characteristic Times g| 239 -- g| II t| Advanced Process Modelling and Model Analysis -- g| 10 t| Basic Tools for Process Model Analysis -- g| 10.1. t| Problem Statements and Solutions g| 251 -- g| 10.2. t| Basic Notions in Systems and Control Theory g| 253 -- g| 10.3. t| Lumped Dynamic Models as Dynamic System Models g| 264 -- g| 10.4. t| State Space Models and Model Linearization g| 269 -- g| 10.5. t| Structural Graphs of Lumped Dynamic Models g| 277 -- g| 11 t| Data Acquisition and Analysis -- g| 11.1. t| Sampling of Continuous Time Dynamic Models g| 286 -- g| 11.2. t| Data Screening g| 289 -- g| 11.3. t| Experiment Design for Parameter Estimation of Static Models g| 294 -- g| 11.4. t| Experiment Design for Parameter Estimation of Dynamic Models g| 295 -- g| 12 t| Statistical Model Calibration and Validation -- g| 12.1. t| Grey-Box Models and Model Calibration g| 300 -- g| 12.2. t| Model Parameter and Structure Estimation g| 302 -- g| 12.3. t| Model Parameter Estimation for Static Models g| 314 -- g| 12.4. t| Identification: Model Parameter and Structure Estimation of Dynamic Models g| 318 -- g| 12.5. t| CSTR: A Case Study of Model Parameter Estimation g| 323 -- g| 12.6. t| Statistical Model Validation via Parameter Estimation g| 330 -- g| 13 t| Analysis of Dynamic Process Models -- g| 13.1. t| Analysis of Basic Dynamical Properties g| 336 -- g| 13.2. t| Analysis of Structural Dynamical Properties g| 341 -- g| 13.3. t| Model Simplification and Reduction g| 350 -- g| 14 t| Process Modelling for Control and Diagnostic Purposes -- g| 14.1. t| Model-Based Process Control g| 364 -- g| 14.2. t| Model-Based Process Diagnosis g| 370 -- g| 14.3. t| Qualitative, Logical and AI Models g| 372 -- g| 15 t| Modelling Discrete Event Systems -- g| 15.1. t| Characteristics and Issues g| 388 -- g| 15.2. t| Approaches to Model Representation g| 388 -- g| 15.3. t| Solution of Discrete Event Dynamic System Models g| 404 -- g| 15.4. t| Analysis of Discrete Event Systems g| 408 -- g| 16 t| Modelling Hybrid Systems -- g| 16.1. t| Hybrid Systems Basics g| 415 -- g| 16.2. t| Approaches to Model Representation g| 420 -- g| 16.3. t| Analysis of Hybrid Systems g| 430 -- g| 16.4. t| Solution of Hybrid System Models g| 431 -- g| 17 t| Modelling Applications in Process Systems -- g| 17.1. t| Copper Converter Dynamics g| 438 -- g| 17.2. t| Destruction of Phenol in Wastewater by Photochemical Reaction g| 445 -- g| 17.3. t| Prefermenter System for Wastewater Treatment g| 451 -- g| 17.4. t| Granulation Circuit Modelling g| 456 -- g| 17.5. t| Industrial Depropanizer using Structural Packing g| 462 -- g| 18 t| Computer Aided Process Modelling -- g| 18.2. t| Industrial Demands on Computer Aided Modelling Tools g| 472 -- g| 18.3. t| Basic Issues in CAPM Tools g| 474 -- g| 18.4. t| Approaches to CAPM Tool Development g| 483 -- g| 19 t| Empirical Model Building -- g| 19.2. t| Modelling Procedure Revisited g| 494 -- g| 19.3. t| Black-Box Modelling g| 497 -- g| 19.4. t| Traps and Pitfalls in Empirical Model Building g| 511 -- g| Appendix t| Basic Mathematic Tools g| 517 -- g| A.1. t| Random Variables and Their Properties g| 517 -- g| A.2. t| Hypothesis Testing g| 521 -- g| A.3. t| Vector and Signal Norms g| 522 -- g| A.4. t| Matrix and Operator Norms g| 523 -- g| A.5. t| Graphs g| 524.
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    a| Manufacturing processes x| Mathematical models.
    700
    1
      
    a| Cameron, I. T.
    999
      
      
    a| T57.6 .H36 2001 w| LC i| X004523581 l| STACKS m| SCI-ENG t| BOOK

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