Dynamic Model Development : Methods, Theory and Applications

S. P. Asprey

ISBN 10: 0444514651 / ISBN 13: 9780444514653

Published by Elsevier BV Aug 2003, 2003

About this Item

Neuware - 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.

Seller Inventory # 9780444514653

Bibliographic Details

• Title: Dynamic Model Development : Methods, Theory and Applications
• Publisher: Elsevier BV Aug 2003
• Publication Date: 2003
• Language: English
• ISBN 10: 0444514651
• ISBN 13: 9780444514653
• Binding: Buch
• Condition: Neu
• Dimensions: 229W x 152H x 16D millimeters 229 millimeters width by 152 millimeters height by 16 millimeters depth
• Weight: 529 grams

About this title

Synopsis

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