不同温度下Mg-Gd-Y稀土镁合金的变形行为表征

The uniaxial tension experiment was used to test the mechanical response of Mg-Gd-Y rare earth magnesium alloy at different temperatures, and the plastic flow behavior was characterized. The results show that with the increase of temperature, the Mg-Gd-Y rare earth magnesium alloy presents thermal softening effect in different degree. The mechanical behavior of this alloy has a coupling effect of strain and temperature. Based on Johnson-Cook, Lim-Huh and an improved polynomial temperature term model, the nonlinear plastic flow behavior of Mg-Gd-Y rare earth magnesium alloy at different temperatures was described. The effect of excitation function, hidden layer, optimization algorithm and the number of neurons on the fitting accuracy of artificial neural network (ANN) model was studied systematically, and the optimization effect of genetic algorithm and particle swarm algorithm was compared. Based on the experimental data, the prediction accuracy of the three mathematical models and ANN was compared comprehensively. It is found that the ANN model has higher prediction accuracy and can accurately describe the nonlinear effect law of temperature on mechanical behavior of Mg-Gd-Y rare earth magnesium alloy.