Peter Englezos, Nicolas Kalogerakis

Applied Parameter Estimation for Chemical Engineers (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book determines adjustable parameters in mathematical models that describe steady state or dynamic systems, presenting the most important optimization methods used for parameter estimation. It focuses on the Gauss-Newton method and its modifications for systems and processes represented by algebraic or differential equation models.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 460
• Erscheinungstermin: 12. Oktober 2000
• Englisch
• ISBN-13: 9780203904695
• Artikelnr.: 60770605

Autorenporträt

Englezos, Peter; Kalogerakis, Nicolas

Inhaltsangabe

Formulation of the parameter estimation problem
computation of parameters in linear models-linear regression
Gauss-Newton method for algebraic models
other nonlinear regression methods for algebraic models
Gauss-Newton method for ordinary differential equation (ODE) models
shortcut estimation methods for ODE models
practical guidelines for algorithm implementation
constrained parameter estimation
Gauss-Newton method for partial differential equation (PDE) models
statistical inferences
design of experiments
recursive parameter estimation
parameter estimation in nonlinear thermodynamic models - cubic equation of state
parameter estimation in nonlinear thermodynamic models - activity coefficients
parameter estimation in chemical reaction kinetic models
parameter estimation in biochemical engineering models
parameter estimation in petroleum engineering. Appendices: the Trebble-Bishnoi equation of state
derivation of the fugacity expression
listings of computer programs
contents of accompanying CD
computer program for example16.1.2
computer program for example 16.3.2.