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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Vydáno v:	Computational materials science Ročník 44; číslo 2; s. 339 - 346
Hlavní autoři:	Chaparro, B.M., Thuillier, S., Menezes, L.F., Manach, P.Y., Fernandes, J.V.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 01.12.2008 Elsevier
Témata:	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
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Abstract	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 former two, in such a way that the result of the genetic algorithm is considered as the initial values for the gradient-based algorithm. The objective of this approach is to improve the performance of the gradient-based algorithm, which is strongly dependent on the initial set of results. The constitutive model used to compare the three different optimization schemes uses the Barlat’91 yield criterion, an isotropic Voce type law and a kinematic Lemaitre and Chaboche law, which is suitable for the case of aluminium alloys. In order to analyse the effectiveness of this optimization procedure, numerical and experimental results for an EN AW-5754 aluminium alloy are compared.
AbstractList	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 former two, in such a way that the result of the genetic algorithm is considered as the initial values for the gradient-based algorithm. The objective of this approach is to improve the performance of the gradient-based algorithm, which is strongly dependent on the initial set of results. The constitutive model used to compare the three different optimization schemes uses the Barlat'91 yield criterion, an isotropic Voce type law and a kinematic Lemaitre and Chaboche law, which is suitable for the case of aluminium alloys. In order to analyse the effectiveness of this optimization procedure, numerical and experimental results for an EN AW-5754 aluminium alloy are compared.
Author	Chaparro, B.M. Thuillier, S. Menezes, L.F. Fernandes, J.V. Manach, P.Y.
Author_xml	– sequence: 1 givenname: B.M. surname: Chaparro fullname: Chaparro, B.M. email: bruno.chaparro@dem.uc.pt organization: Escola Superior de Tecnologia de Abrantes, Instituto Politécnico de Tomar, Rua de 17 de Agosto de 1808, 2200-370 Abrantes, Portugal – sequence: 2 givenname: S. surname: Thuillier fullname: Thuillier, S. organization: Laboratoire de Génie Mécanique et Matériaux (LG2M), Université de Bretagne-Sud, Rue de Saint Maudé, BP 92116-56321 Lorient cedex, France – sequence: 3 givenname: L.F. surname: Menezes fullname: Menezes, L.F. organization: CEMUC, Departamento de Engenharia Mecânica, Universidade de Coimbra, Pinhal de Marrocos, 3030-201 Coimbra, Portugal – sequence: 4 givenname: P.Y. surname: Manach fullname: Manach, P.Y. organization: Laboratoire de Génie Mécanique et Matériaux (LG2M), Université de Bretagne-Sud, Rue de Saint Maudé, BP 92116-56321 Lorient cedex, France – sequence: 5 givenname: J.V. surname: Fernandes fullname: Fernandes, J.V. organization: CEMUC, Departamento de Engenharia Mecânica, Universidade de Coimbra, Pinhal de Marrocos, 3030-201 Coimbra, Portugal
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Keywords	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
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Snippet	This paper presents two procedures for the identification of material parameters, a genetic algorithm and a gradient-based algorithm. These algorithms enable...
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SubjectTerms	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
Title	Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms
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