Studying the micromechanical behaviors of a polycrystalline metal by artificial neural networks

Though physics-based crystal plasticity models are able to accurately predict the material response under complex loading conditions, the high computational cost limits their engineering applications. Machine learning techniques, widely used to understand and predict data trends, can provide advantageous computational efficiency over conventional numerical techniques. In the current work, an artificial neural network (ANN) model is proposed and...