On the determination of material parameters for internal variable thermoelastic-viscoplastic constitutive models

被引:77
作者
Andrade-Campos, A.
Thuillier, S.
Pilvin, P.
Teixeira-Dias, F.
机构
[1] Univ Aveiro, Dept Engn Mecan, P-3810193 Aveiro, Portugal
[2] Univ Bretagne Sud, Lab Genie Mecan & Mat, LG2M, F-56231 Lorient, France
关键词
parameter identification; thermoelastic viscoplastic constitutive model; optimization; gradient-based method; evolutionary algorithm; EVOLUTIONARY ALGORITHM; IDENTIFICATION; DEFORMATION; ALUMINUM; OPTIMIZATION; BEHAVIOR; COMPUTATION; SIMULATION; DESIGN;
D O I
10.1016/j.ijplas.2006.09.002
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The work presented in this paper deals with the determination of material parameters used in internal variable constitutive models. In order to determine the best suited material parameter set, in the less computationally expensive way, two optimization approaches are used: (i) a gradient-based method and (ii) a continuous evolutionary algorithm (EA) method. The first approach uses a combination of the steepest descent gradient and the Levenberg-Marquardt techniques. The performance of this method is known to be highly dependent on the starting et of parameters and its results are often inconsistent. The EA-based technique provides a better way to determine an optimized set of parameters (the overall minimum). Thus, the difficulty of choosing a starting set of parameters for this process is minor. The main application in this work is a 16 parameter thermoelastic-viscoplastic constitutive model. Experimental data was obtained from tensile and shear tests at different temperatures and used to compare with numerical results and to determine the correct set of material parameters. Numerical constraints were introduced to enforce physical requirements on the material parameters. Both methods are used to determine the 12 material parameters needed for an AA1050-O aluminium alloy. Although the EA-based method achieved a slightly better result, it proved to be computationally more expensive than the gradient-based method. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1349 / 1379
页数:31
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