An exponential strain dependent Rusinek–Klepaczko model for flow stress prediction in austenitic stainless steel 304 at elevated temperatures

In this paper, to predict flow stress of Austenitic Stainless Steel (ASS) 304 at elevated temperatures the extended Rusinek–Klepaczko (RK) model has been modified using an exponential strain dependent term for dynamic strain aging (DSA) region. Isothermal tensile tests are conducted on ASS 304 for a temperature range of 323–923 K with an interval of 50 K and at strain rates of 0.0001 s−1, 0.001 s−1, 0.01 s−1 and 0.1 s−1. DSA phenomenon is observed from 623 to 923 K at 0.0001 s−1, 0.001 s−1 and 0.01 s−1. Material constants are calculated using data obtained from these tensile tests for non-DSA and DSA region separately. The predicted results from the RK model are compared with the experimental data to check the accuracy of the constitutive relation. It is observed that to find out the constants of this model, some initial assumptions are required, and these initial values affect the predicted values. Hence, Genetic Algorithm (GA) is used to optimize the constants for RK model. Statistical measures such as the correlation coefficient, the average absolute error and standard deviation are used to measure the accuracy of the model. The resulting values of the correlation coefficient for ASS 304 for non-DSA and DSA region using modified extended RK model are 0.9828 and 0.9701. This modified, extended RK model is compared with Johnson–Cook (JC), Zerilli–Armstrong (ZA) and Arrhenius models and it is observed that specifically in DSA region, the modified extended RK model gives highly accurate predictions.