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Process Modelling and Model Analysis : Volume 4 - John Perkins

Process Modelling and Model Analysis

Volume 4

Hardcover Published: 12th June 2001
ISBN: 9780121569310
Number Of Pages: 543

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This book describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents.
To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises.
* Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation.
* Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling
* Illustrates the notions, tools, and techniques of process modeling with examples and advances applications

Introductionp. xiii
Fundamental Principles and Process Model Development
The Role of Models in Process Systems Engineering
The Idea of a Modelp. 4
Model Application Areas in PSEp. 7
Model Classificationp. 10
Model Characteristicsp. 12
A Brief Historical Review of Modelling in PSEp. 13
Summaryp. 17
Review Questionsp. 17
Application Exercisesp. 17
A Systematic Approach to Model Building
The Process System and the Modelling Goalp. 20
Mathematical Modelsp. 22
A Systematic Modelling Procedurep. 24
Ingredients of Process Modelsp. 32
Summaryp. 36
Review Questionsp. 36
Application Exercisesp. 37
Conservation Principles
Thermodynamic Principles of Process Systemsp. 42
Principle of Conservationp. 51
Balance Volumes in Process System Applicationsp. 58
Summaryp. 61
Review Questionsp. 62
Application Exercisesp. 62
Constitutive Relations
Transfer Rate Equationsp. 65
Reaction Kineticsp. 70
Thermodynamical Relationsp. 72
Balance Volume Relationsp. 75
Equipment and Control Relationsp. 75
Summaryp. 79
Review Questionsp. 79
Application Exercisesp. 80
Dynamic Models--Lumped Parameter Systems
Characterizing Models and Model Equation Setsp. 83
Lumped Parameter Models--Initial Value Problems (IVPs)p. 84
Conservation Balances for Massp. 86
Conservation Balances for Energyp. 89
Conservation Balances for Momentump. 95
The Set of Conservation Balances for Lumped Systemsp. 98
Conservation Balances in Intensive Variable Formp. 99
Dimensionless Variablesp. 101
Normalization of Balance Equationsp. 102
Steady-State Lumped Parameter Systemsp. 103
Analysis of Lumped Parameter Modelsp. 104
Stability of the Mathematical Problemp. 114
Summaryp. 117
Review Questionsp. 118
Application Exercisesp. 118
Solution Strategies for Lumped Parameter Models
Process Engineering Example Problemsp. 124
Ordinary Differential Equationsp. 125
Basic Concepts in Numerical Methodsp. 126
Local Truncation Error and Stabilityp. 129
Stability of the Numerical Methodp. 133
Key Numerical Methodsp. 137
Differential-Algebraic Equation Solution Techniquesp. 149
Summaryp. 155
Review Questionsp. 156
Application Exercisesp. 156
Dynamic Models--Distributed Parameter Systems
Development of DPS Modelsp. 163
Examples of Distributed Parameter Modellingp. 174
Classification of DPS Modelsp. 182
Lumped Parameter Models for Representing DPSsp. 185
Summaryp. 186
Review Questionsp. 187
Application Exercisesp. 187
Solution Strategies for Distributed Parameter Models
Areas of Interestp. 191
Finite Difference Methodsp. 192
Method of Linesp. 201
Method of Weighted Residualsp. 203
Orthogonal Collocationp. 206
Orthogonal Collocation for Partial Differential Equationsp. 216
Summaryp. 218
Review Questionsp. 218
Application Exercisesp. 219
Process Model Hierarchies
Hierarchy Driven by the Level of Detailp. 225
Hierarchy Driven by Characteristic Sizesp. 233
Hierarchy Driven by Characteristic Timesp. 239
Summaryp. 245
Further Readingp. 246
Review Questionsp. 246
Application Exercisesp. 246
Advanced Process Modelling and Model Analysis
Basic Tools for Process Model Analysis
Problem Statements and Solutionsp. 251
Basic Notions in Systems and Control Theoryp. 253
Lumped Dynamic Models as Dynamic System Modelsp. 264
State Space Models and Model Linearizationp. 269
Structural Graphs of Lumped Dynamic Modelsp. 277
Summaryp. 281
Review Questionsp. 281
Application Exercisesp. 282
Data Acquisition and Analysis
Sampling of Continuous Time Dynamic Modelsp. 286
Data Screeningp. 289
Experiment Design for Parameter Estimation of Static Modelsp. 294
Experiment Design for Parameter Estimation of Dynamic Modelsp. 295
Summaryp. 296
Further Readingp. 296
Review Questionsp. 296
Application Exercisesp. 297
Statistical Model Calibration and Validation
Grey-Box Models and Model Calibrationp. 300
Model Parameter and Structure Estimationp. 302
Model Parameter Estimation for Static Modelsp. 314
Identification: Model Parameter and Structure Estimation of Dynamic Modelsp. 318
CSTR: A Case Study of Model Parameter Estimationp. 323
Statistical Model Validation via Parameter Estimationp. 330
Summaryp. 331
Further Readingp. 331
Review Questionsp. 331
Application Exercisesp. 332
Analysis of Dynamic Process Models
Analysis of Basic Dynamical Propertiesp. 336
Analysis of Structural Dynamical Propertiesp. 341
Model Simplification and Reductionp. 350
Summaryp. 359
Further Readingp. 359
Review Questionsp. 360
Application Exercisesp. 361
Process Modelling for Control and Diagnostic Purposes
Model-Based Process Controlp. 364
Model-Based Process Diagnosisp. 370
Qualitative, Logical and AI Modelsp. 372
Summaryp. 384
Further Readingp. 384
Review Questionsp. 385
Application Exercisesp. 385
Modelling Discrete Event Systems
Characteristics and Issuesp. 388
Approaches to Model Representationp. 388
Solution of Discrete Event Dynamic System Modelsp. 404
Analysis of Discrete Event Systemsp. 408
Summaryp. 410
Further Readingp. 411
Review Questionsp. 412
Application Exercisesp. 412
Modelling Hybrid Systems
Hybrid Systems Basicsp. 415
Approaches to Model Representationp. 420
Analysis of Hybrid Systemsp. 430
Solution of Hybrid System Modelsp. 431
Summaryp. 434
Further Readingp. 434
Review Questionsp. 435
Application Exercisesp. 436
Modelling Applications in Process Systems
Copper Converter Dynamicsp. 438
Destruction of Phenol in Wastewater by Photochemical Reactionp. 445
Prefermenter System for Wastewater Treatmentp. 451
Granulation Circuit Modellingp. 456
Industrial Depropanizer using Structural Packingp. 462
Summaryp. 469
Computer Aided Process Modelling
Introductionp. 472
Industrial Demands on Computer Aided Modelling Toolsp. 472
Basic Issues in CAPM Toolsp. 474
Approaches to CAPM Tool Developmentp. 483
Summaryp. 492
Empirical Model Building
Introductionp. 493
The Modelling Procedure Revisitedp. 494
Black-Box Modellingp. 497
Traps and Pitfalls in Empirical Model Buildingp. 511
Summaryp. 515
Further Readingp. 515
Review Questionsp. 516
Application Exercisesp. 516
Basic Mathematic Toolsp. 517
Random Variables and Their Propertiesp. 517
Hypothesis Testingp. 521
Vector and Signal Normsp. 522
Matrix and Operator Normsp. 523
Graphsp. 524
Bibliographyp. 527
Indexp. 535
Table of Contents provided by Syndetics. All Rights Reserved.

ISBN: 9780121569310
ISBN-10: 0121569314
Series: Process Systems Engineering
Audience: Tertiary; University or College
Format: Hardcover
Language: English
Number Of Pages: 543
Published: 12th June 2001
Publisher: Elsevier Science Publishing Co Inc
Country of Publication: US
Dimensions (cm): 24.4 x 17.1  x 3.18
Weight (kg): 1.24