基于缺口试件应力状态试验的Johnson-Cook模型参数反演标定方法

Inverse Determination Method of Johnson-Cook Model Parameters Based on the Stress State Test of Notched Specimens

Johnson-Cook模型是适用于金属高应变率、大变形的强动载材料模型之一,其对应于材料的参数标定是模型应用的关键。由于没有考虑复杂应力状态对材料性能的影响,在不同应力状态下使用传统标定方法标定的模型进行模拟计算,计算结果与实际情况存在显著的差异。为了减小这种差异,使用6005A-T6铝合金,设计用以表征不同应力状态的缺口试件,在应变率4×10^(-4)s^(-1)条件进行准静态单向拉伸试验。使用一种基于遗传算法的反演标定方法,将不同应力状态条件下的试验数据纳入到遗传算法的训练集中,以Matlab-LS-DYNA联合编程进行数据交互与集成,从而获得标定参数的最优解。结果表明,该方法标定的材料模型参数弥补了传统方法的不足,在复杂应力状态条件下具有更好的适用性。

Johnson-Cook model is one of the material models suitable for metals with high strain rate,large deformation and strong dynamic load.The determination of parameters corresponding to the material is the key to the application of the model.Since the influence of complex stress state on material properties is not considered,when the model determined by traditional method is used for simulation,there is a significant difference between the calculated results and the actual situation under different stress conditions.Aimed at reduction of such difference,the notched specimens of 6005 A-T6 aluminum alloy are designed to characterize different stress states,and the quasi-static uniaxial tensile tests are carried out under the condition of strain rate 4×10^(-4)S^(-1).Then,an inverse determination method based on genetic algorithm is proposed,in which the test data under different stress states are included in the training set of genetic algorithm.Using Matlab programming,the data interaction and process integration of optimization algorithm and LS-DYNA simulation are realized.By running the program,the optimal solution of model parameters is obtained.The results show that the model parameters obtained by this method make up for the shortcomings of traditional methods.In the complex stress state,it has better applicability.