Книга Dynamic Model Development: Methods, Theory and Applications S. Macchietto

Dynamic Model Development: Methods, Theory and Applications

Автор: S. Macchietto
Език: Английски език
Корици: С твърди корици
Издател: Elsevier Science
Наличност: Външен склад
Изпращаме след 9-15 дни
572.09 1 118.91 лв
Detailed mathematical models are increasingly being used by companies to gain competitive advantage...

Информация за книгата

Автор
Език
Английски език
Корици
Книга - С твърди корици
Издадена
2003
страници
266
EAN
9780444514653
ISBN
0444514651
Enbook ID
04611200
Издател
Теглоt
530
Размери
165 x 240 x 16

Пълно описание

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. It contains wide coverage of statistical methods applied to process modelling. It serves as a recent compilation of dynamic model building tools. It presents several examples of applying advanced statistical and modelling methods to real process systems problems.

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