Determination of residual stress and strain-hardening exponent using artificial neural networks

Through dimensional analysis of indentation parameters in this study, we propose an artificial neural network (ANN) model to extract the residual stress and strain-hardening exponent based on spherical indentation. The relationships between indentation parameters and the residual stress and material properties are numerically calibrated through training and validation of the ANN model. They enable the direct mapping of the characteristics of the indentation parameters to the residual stress and the elastic-plastic material properties. The proposed ANN model can be used to quickly and effectively determine the residual stress and strain-hardening exponent.