Parameters Determination of Hardening Model for Ultra-high Strength Steel Based on Modified Genetic Algorithm and Bending Spring Back Prediction

doi:10.3901/JME.2024.12.240

Abstract

Abstract: For the severe spring back problem of ultra-high strength steel (UHSS) used in special purpose vehicles during the bending process, a method for determining the parameters of the hardening model of the UHSS based on an improved genetic algorithm is proposed and accurate prediction of the bending spring-back of the UHSS is achieved. Taking the UHSS 6252 as the example, a Yoshida-Uemori hardening model framework considering the strain-hardening behavior and Bauschinger effect of the UHSS is constructed. Then, the material properties of the hardening model framework are accurately determined by combining the modified genetic algorithm and the finite element simulation software LS-DYNA. Finally, the spring back in bending process is predicted for the UHSS 6252 based on the DYNAFORM platform. The actual bending test shows that the error of the spring-back angle between the simulation and experiment is within 2%, which verifies the reliability of the calibrated hardening model parameters for the UHSS and demonstrates that the Yoshida-Uemori hardening model supported by this parameter set can well describe the dynamic characteristics of the UHSS. The proposed method provides effective guidance for the design of high-precision forming processes for ultra-high-strength steel components.

Key words: modified genetic algorithm, ultra-high strength steel, hardening model, bending, spring back prediction

CLC Number:

TG318

LIU Chengshang, CHEN Rui, LI Fang, WANG Meng, XU Wujiao. Parameters Determination of Hardening Model for Ultra-high Strength Steel Based on Modified Genetic Algorithm and Bending Spring Back Prediction[J]. Journal of Mechanical Engineering, 2024, 60(12): 240-249.

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