基于混合数值算法的车用钢材料参数反求

Reverse of Material Parameter of High-strength Steel for Vehicles Based on Hybrid Numerical Algorithm

为进一步提高汽车碰撞仿真的准确性,深入研究了车用高强钢材料的本构模型,采用实验与有限元仿真混合数值算法,提出了基于多岛遗传算法(MIGA)的反求材料本构模型的参数。数据显示试验结果与优化的参数结果有着较高的一致性,能够准确反映在动态冲击载荷下的材料的流变行为,从而提高台车碰撞仿真精度。为汽车结构碰撞研究提供精确的仿真基础,具有一定的指导意义。

The constitutive model of the material was studied in order to further improve the accuracy of the simulation.The experimental and finite element simulation hybrid numerical algorithm was used to propose the parameters of the constitutive model based on multi island genetic algorithm (MIGA).The final results show that,in terms of the peak acceleration and the number of thin wall deformation and folding,it is obviously better to consider the strain rate effect than not to consider the strain rate.The reversed material parameters are highly consistent with the experimental curves and can accurately reflect the rheological behavior of the material under dynamic impact loading.The precise simulation foundation for automotive structural collision can be provided by the research.This research has certain guiding significance.