Development of constitutive models for dynamic strain aging regime in Austenitic stainless steel 304

The experimental stress–strain data from isothermal tensile tests over a wide range of temperatures (623–923 K at an interval of 50 K), strains (0.02–0.30 at an interval of 0.02) and strain rates (0.0001, 0.001, 0.01, 0.1 s−1) were employed to determine the Dynamic Strain Aging (DSA) regime and to formulate a suitable constitutive model to predict the elevated-temperature deformation behavior in DSA regime of Austenitic Stainless Steel (ASS) 304. Four models, namely, Johnson Cook (JC) model, modified Zerilli–Armstrong (m-ZA) model, modified Arrhenius type equations (m-Arr) and Artificial Neural Networks (ANNs), were investigated. Suitability of these models was evaluated by comparing the correlation coefficient, average absolute error and its standard deviation. It was observed that JC, m-ZA and m-Arr model could not effectively predict flow stress behavior of ASS304 in DSA regime, while the predictions by ANN model are found to be in good agreement with the experimental data.