Flow stress prediction in warm forming conditions of AZ31 magnesium alloy sheets using an ANN-based model

Tensile tests in extended ranges of strain rate (10-3–1 s-1) and temperature (200-300°C) were performed on AZ31 magnesium alloy sheets in order to investigate their effect on the flow curve. The influence of fibre orientation was also taken into account. These data were used to build an artificial neural network model able to predict the flow curve.
The validity of the model was proven by comparing predicted and experimental flow curves using the leave k-out method. It was observed that the artificial neural network was able to predict both the curve shape and stress levels as a function of the process parameters.