Prediction of mechanical properties of extra deep drawn steel in blue brittle region using Artificial Neural Network

Blue brittle region also known as dynamic strain ageing (DSA) regime is very important in the materials because in this region material properties behave in very unpredictable ways. In this work, Artificial Neural Network (ANN) models are developed for the prediction of mechanical properties such as yield strength (YS), ultimate tensile strength (UTS), % elongation, strength coefficient (K) and strain hardening exponent (n) for the extra deep drawn (EDD) quality steel in blue brittle region. To calculate the mechanical properties at elevated temperatures, experiments were conducted at the interval of 25 °C from room temperature till 700 °C in three rolling directions. Based on the experimental results, the blue brittle region for EDD steel is identified between 350 °C and 450 °C and ANN model is trained in all the three rolling directions. Trained up ANN model is tested with the experimental results at two different temperatures with in blue brittle region. Experimental and modeling errors in the prediction of mechanical properties are found within the permissible range.