Application of Support Vector Regression on Mechanical Properties of Austenitic Stainless Steel 304 at Elevated Temperatures

Austenitic Stainless Steel grade 304 is a very important alloy used in various high temperature applications which make it important to study their mechanical properties at elevated temperatures. In this work, the mechanical properties such as Ultimate Tensile Strength (UTS), Yield Strength (YS), % elongation, Strain Hardening Exponent (n) and Strength Coefficient (K) are evaluated based on the experimental data obtained from the uniaxial isothermal tensile tests performed at an interval of 50 degrees C from 50 degrees Cto 650 degrees C and at three different strain rates (0.0001, 0.001 and 0.01s(-1)). Support Vector Regression has been used to train for prediction of these mechanical properties. The trained SVR model gives an excellent correlation coefficient and the error values are also significantly low which represents a good accuracy of the model. (C) 2015 Elsevier Ltd. All rights reserved.