Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

This paper presents two procedures for the identification of material parameters, a genetic algorithm and a gradient-based algorithm. These algorithms enable both the yield criterion and the work hardening parameters to be identified. A hybrid algorithm is also used, which is a combination of the fo...

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Veröffentlicht in:	Computational materials science Jg. 44; H. 2; S. 339 - 346
Hauptverfasser:	Chaparro, B.M., Thuillier, S., Menezes, L.F., Manach, P.Y., Fernandes, J.V.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.12.2008 Elsevier
Schlagworte:	Anisotropy Condensed matter: structure, mechanical and thermal properties Deformation and plasticity (including yield, ductility, and superplasticity) Engineering Sciences Exact sciences and technology Mechanical and acoustical properties of condensed matter Mechanical properties of solids Optimization Parameter identification Physics Plasticity Stamping Work hardening Yield criteria Work hardening 62.20.-x 81.20.Hy Parameter identification Optimization 62.20.Fe Yield criteria Stamping 07.10.-h 81.05.-t Anisotropy Plasticity 81.40.Lm 81.70.Bt Constitutive equation Yield criterion Optimization method Genetic algorithms Aluminium alloys Hybrid model Strain hardening
ISSN:	0927-0256, 1879-0801
Online-Zugang:	Volltext
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