Application of Support Vector Regression on Mechanical Properties of Austenitic Stainless Steel 304 at Elevated Temperatures. (2015)

• Record Type: Journal Article
• Authors: Kanumuri, Lakshmi; Srishuka, M.; Gupta, Amit Kumar; Singh, Swadesh Kumar
• Is Part Of: Materials today. Volume 2:Number 4/5(2015)
• Page Start: 1479
• Page End: 1486
• Publication Date: 2015
• Subjects: Austenitic Stainless Steel -- Mechanical Properties -- Tensile Test -- Support Vector Regression.; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2015.07.073
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: 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 ( Y S ), % 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 0 C from 50 0 Cto 650 0 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.