Process Modelling and Model Analysis

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Edition: 1

Series: Process systems engineering 4

ISBN: 9780121569310, 0-12-156931-4

Size: 25 MB (26007044 bytes)

Pages: 3-543/561

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K.M. Hangos and I.T. Cameron (Eds.)9780121569310, 0-12-156931-4

Process modeling is one of the key aspects of process systems engineering. It is a significant activity in most major companies around the world, driven by applications such as process optimization, design, and control.Process Modeling and Modeling Analysis gives a comprehensive treatment of process modeling for the student, researcher, and industrial practitioner. It presents a systematic approach to modeling covering model formulation, documentation, analysis, solution, and validation. Process models depend not only on the process itself, but also on the modeling goal. This book, therefore, places its main emphasis on process models for dynamic simulation and process control purposes.This book:* 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

Table of contents :
Content:
Introduction
Pages xiii-xvi

1 The role of models in process systems engineering
Pages 3-18

2 A systematic approach to model building
Pages 19-40

3 Conservation principles
Pages 41-63

4 Constitutive relations
Pages 65-82

5 Dynamic models—Lumped parameter systems
Pages 83-122

6 Solution strategies for lumped parameter models
Pages 123-161

7 Dynamic models—Distributed parameter systems
Pages 163-189

8 Solution strategies for distributed parameter models
Pages 191-222

9 Process model hierarchies
Pages 223-247

10 Basic tools for process model analysis
Pages 251-284

11 Data acquisition and analysis
Pages 285-297

12 Statistical model calibration and validation
Pages 299-334

13 Analysis of dynamic process models
Pages 335-362

14 Process modelling for control and diagnostic purposes
Pages 363-386

15 Modelling discrete event systems
Pages 387-414

16 Modelling hybrid systems
Pages 415-436

17 Modelling applications in process systems
Pages 437-469

18 Computer aided process modelling
Pages 471-492

19 Empirical model building
Pages 493-516

Appendix: Basic mathematical tools
Pages 517-525

Bibliography
Pages 527-533

Index
Pages 535-543

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