Comparison of Prediction Models for the Hot Deformation Behavior of Cast Mg–Zn–Y Alloy

Abstract

Alloying magnesium with rare-earth elements is an efficient method to improve the high-temperature properties of magnesium. In this study, the hot deformation behavior of Mg–8Zn–4Y was studied for the temperatures 523–673 K and the strain rates 0.001–0.3 s−1. The flow stress varied with strain, strain rate, and temperature and was found to increase with a decrease in temperature or an increase in strain rate. The experimental data were used to develop four different prediction models for the flow stress, viz. strain-compensated Arrhenius equation, Johnson–Cook model, modified Johnson–Cook model, and backpropagated artificial neural network model. Further, the predictive capability of the models was compared using standard statistical parameters. The backpropagated artificial neural network model was found to predict the flow behavior most accurately. For situations where a physical insight into the material response is needed, the strain-compensated Arrhenius equation can be used.