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Parameter identification of chaboche material model using indantation test data and inverse approach

Authors: Cermak, Martin; Halama, Radim; Karasek, Tomas; Rojicek, Jaroslav;

Parameter identification of chaboche material model using indantation test data and inverse approach

Abstract

In this paper genetic algorithm and sensitivity analysis are used to identify 6 parameters of Chaboche kinematic hardening model using repeated Finite element (FE) simulations of indentation test. Five of them are material constants of Chaboche kinematic hardening model itself. The last one represents the stiffness of the foundation and the indenter. To obtain experimental data indentation test under cyclic loading on universal tensile testing machine was performed. Because for sensitivity analysis to obtain all possible combinations of parameters and its values large number of simulation have to be performed supercomputer Anselm hosted by IT4Innovation has been used. Advantage of using supercomputer is that every simulation could use multiple cores which will reduce computational time. Moreover, since each simulation is independent, computational time could be further reduced by performing multiple simulations at the same time. It is clear from the comparison of both methods that the genetic algorithm is very good choice for the parameter estimation.

Country
Spain
Keywords

Finite element method, Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits, Genetic Algorithm, Sensitivity Analysis, Inverse Approach, Finite Element Method, Indentation, Ratcheting, Elements finits, Mètode dels, Coupled problems (Complex systems) -- Numerical solutions, :Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits [Àrees temàtiques de la UPC]

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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