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A Robust Inverse Method Based on Least Square Support Vector Regression for Johnson-cook Material Parameters

Hu Wang1, Weiyi Li1, Guangyao Li1

State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, 410082, China

Computers, Materials & Continua 2012, 28(2), 121-146. https://doi.org/10.3970/cmc.2012.028.121

Abstract

The purpose of this study is to propose a robust inverse method for estimating Johnson-Cook material parameters. The method is shown through illustrative examples for two different advanced high strength steel (AHSS) materials (DP980 and TRIP780) using set of data from impact experiments with different velocities. Compared with widely mixed numerical experimental methods, the suggested inverse method has the capability to guarantee the robustness of the obtained parameters by considering uncertainties. The inverse problem is converted into multi-objective optimization problems. Furthermore, in order to improve the performance in efficiency and accuracy, metamodeling techniques and global optimization method are integrated. The final results demonstrate that the experimental and simulation curves are well matched based on identified by the suggested robust inverse method.

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APA Style
Wang, H., Li, W., Li, G. (2012). A robust inverse method based on least square support vector regression for johnson-cook material parameters. Computers, Materials & Continua, 28(2), 121-146. https://doi.org/10.3970/cmc.2012.028.121
Vancouver Style
Wang H, Li W, Li G. A robust inverse method based on least square support vector regression for johnson-cook material parameters. Comput Mater Contin. 2012;28(2):121-146 https://doi.org/10.3970/cmc.2012.028.121
IEEE Style
H. Wang, W. Li, and G. Li "A Robust Inverse Method Based on Least Square Support Vector Regression for Johnson-cook Material Parameters," Comput. Mater. Contin., vol. 28, no. 2, pp. 121-146. 2012. https://doi.org/10.3970/cmc.2012.028.121



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