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Parameter identification theory of a complex model based on global optimization method

Content Provider	Springer Nature Link
Author	Qu, Jie Jin, QuanLin Xu, BingYe
Copyright Year	2008
Abstract	With the development of computer technology and numerical simulation technology, computer aided engineering (CAE) technology has been widely applied to many fields. One of the main obstacles, which hinder the further application of CAE technology, is how to successfully identify the parameters of the selected model. An elementary framework for parameter identification of a complex model is provided in this paper. The framework includes the construction of objective function, the design of the optimization method and the evaluation of the identified results, etc. The parameter identification process is described in this framework, taking the parameter identification of the superplastic constitutive model considering grain growth for Ti-6Al-4V at 927°C as an example. The objective function is the weighted quadratic sums of the difference between the experimental and computational data for the stress-strain relationship and the grain growth relationship; the designed optimization method is a hybrid global optimization method, which is based on the feature of the objective function and incorporates the strengths of genetic algorithm (GA), the Levenberg-Marquardt algorithm and the augmented Gauss-Newton algorithm. The reliability evaluation of parameter identification result is made through the comparison between the calculated and experimental results and between the theoretical values of the parameters and the identified ones.
Starting Page	1722
Ending Page	1732
Page Count	11
File Format	PDF
ISSN	16721799
Journal	Science in China Series G
Volume Number	51
Issue Number	11
e-ISSN	18622844
Language	English
Publisher	SP Science in China Press
Publisher Date	2008-10-04
Publisher Place	Heidelberg
Access Restriction	Subscribed
Subject Keyword	constitutive model parameter identification theory inverse analysis global optimization Astronomy Mechanics, Fluids, Thermodynamics Physics
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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