Hybrid Inverse Parameter Identification of Fully Coupled Ductile Damage Model for Steel Sheet DP600 with Two Different A
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JMEPEG (2019) 28:3149–3156 https://doi.org/10.1007/s11665-019-04087-y
Hybrid Inverse Parameter Identification of Fully Coupled Ductile Damage Model for Steel Sheet DP600 with Two Different Algorithms: Trust Region and Genetic Algorithms Ke Cao, Zhen-ming Yue, Xiao-di Zhao, Jiashuo Qi, and Jun Gao (Submitted March 28, 2018; in revised form August 20, 2018; published online May 13, 2019) Ductile damage model has been widely regarded as a valuable method to predict the failure of sheet metal. Based on the thermodynamic theory and continuum damage mechanics, the fully coupled ductile damage model can be developed, which also can better predict the initiation and growth of the fracture. But the identifications of model parameters with theoretical methodology are difficult due to the complex coupling relationships existing among all state variables. The inverse methodology is regarded as a good method to resolve the problem. In this paper, the recently proposed fully coupled ductile damage model is chosen to investigate the deformation behavior of DP600 steel, in which the mixed saturation isotropic and kinematic hardenings are taken into account and fully coupled with the ductile damage. During the identification process, the least square formula of the error between experimental and numerical results is selected as the target function. The trust region algorithm and genetic algorithm are used with the help of MATLAB for the identification of three damage parameters. Finally, by comparing the experimental and numerical results, the validations of two algorithms are proved. The efficiency of the optimization process with trust region algorithm is higher, but with lower accuracy. Meanwhile, the optimization process is greatly affected by the chosen initial values of the ductile damage parameters. Keywords
adaptive algorithm, ductile damage, identification, inverse methodology, simulation
1. Introduction With the gradual application of lightweight design in industrial production, high-strength steel and high-strength aluminum alloy materials are widely used in many industrial products. However, due to the weakness of ductility, how to accurately predict the deformation and failure behavior in metal forming becomes one of the key problems. Finite element method (FEM) is an effective approach to simulate the forming behavior, and the prediction precision is highly dependent on the constitutive model and the parameter identification accuracy. So, it is very important and valuable to give an efficient parameter identification methodology. Normally, the models for damage prediction of metallic materials can be divided into two categories: coupled damage model and uncoupled damage model according to whether the damage affects other state variables, the yield function, etc. The failure criteria of uncoupled damage models can be based on the maximum or equivalent stress and strain, plastic work, plastic dissipation, and other parameters. In early research, it Ke Cao, Zhen-ming Yue, Xiao-di Zhao, Jiashuo Qi, and Jun Gao, School of Mechan
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