Research Catalog

Title

Process modelling and model analysis / K.M. Hangos, I.T. Cameron.

Author

Hangos, K. M. (Katalin M.)

Publication

San Diego : Academic Press, ©2001.

Items in the Library & Off-site

Details

Additional Authors

Cameron, Ian (Ian Thomas)

Description

xvi, 543 pages : illustrations; 26 cm.

Series Statement

Process systems engineering ; v. 4

Uniform Title

Process systems engineering ; v. 4.

Subject

• Chemical processes > Mathematical models
• Chemical processes > Computer simulation
• Prozessmodell
• Processos químicos (simulação computacional)
• Modelos matemáticos

Bibliography (note)

• Includes bibliographical references (p. 527-533) and index.

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.

ISBN

• 0121569314
• 9780121569310

LCCN

00112073

OCLC

• ocm47402346
• 47402346
• SCSB-9267596

Owning Institutions

Princeton University Library