Dynamic Model Development

S.P. Asprey and S. Macchietto (Eds.)978-0-444-51465-3

Detailed mathematical models are increasingly being used by companies to gain competitive advantage through such applications as model-based process design, control and optimization. Thus, building various types of high quality models for processing systems has become a key activity in Process Engineering. This activity involves the use of several methods and techniques including model solution techniques, nonlinear systems identification, model verification and validation, and optimal design of experiments just to name a few. In turn, several issues and open-ended problems arise within these methods, including, for instance, use of higher-order information in establishing parameter estimates, establishing metrics for model credibility, and extending experiment design to the dynamic situation.The material covered in this book is aimed at allowing easier development and full use of detailed and high fidelity models. Potential applications of these techniques in all engineering disciplines are abundant, including applications in chemical kinetics and reaction mechanism elucidation, polymer reaction engineering, and physical properties estimation. On the academic side, the book will serve to generate research ideas.- Contains wide coverage of statistical methods applied to process modelling- Serves as a recent compilation of dynamic model building tools- Presents several examples of applying advanced statistical and modelling methods to real process systems problems

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Table of contents :
Content:
Foreword
Page v
S. Asprey, S. Macchietto

Methodological aspects in the modelling of novel unit operations Original Research Article
Pages 1-20
H. Haario, I. Turunen

Dynamic modelling, nonlinear parameter fitting and sensitivity analysis of a living free-radical polymerization reactor Original Research Article
Pages 21-39
Antonio Flores-Tlacuahuac, Enrique Saldívar-Guerra, Ramiro Guerrero-Santos

An investigation of some tools for process model indentification for prediction Original Research Article
Pages 41-62
Niels Rode Kristensen, Henrik Madsen, Sten Bay Jørgensen

Multivariate weighted least squares as an alternative to the determinant criterion for multiresponse parameter estimation Original Research Article
Pages 63-84
P.W. Oxby, T.A. Duever, P.M. Reilly

Model selection: An overview of practices in chemical engineering Original Research Article
Pages 85-104
Peter J.T. Verheijen

Statistical dynamic model building: Applications of semi-infinite programming Original Research Article
Pages 105-139
Steven P. Asprey

Non-constant variance and the design of experiments for chemical kinetic models Original Research Article
Pages 141-158
Anthony C. Atkinson

A continuous-time hammerstein approach working with statistical experimental design Original Research Article
Pages 159-173
Derrick K. Rollins

Process design under uncertainty: Robustness criteria and value of information Original Research Article
Pages 175-208
F.P. Bernardo, P.M. Saraiva, E.N. Pistikopoulos

A modelling tool for different stages of the process life Original Research Article
Pages 209-249
Mauricio Sales-Cruz, Rafiqul Gani

Other papers presented at the workshop
Page 251

Author index
Page 253

Subject index
Pages 255-257