Prediction for Mechanical Properties of Lean Duplex Stainless Steel by Using Random Forest

Abstract

Lean duplex stainless steel (LDSS), which is expected to apply to infrastructures, exhibits rounded shape of stress-strain curve. For this reason, a constitutive equation which is able to accurately express the curve is required for the ultimate strength analysis of LDSS structures. Authours have already proposed MRO curve as this kind of equation. However, not only 0.2% proof stress and tensile strength, which are specified in common material standard and a mill certificate, but also mechanical properties such as proportion limit etc are needed to describe the equation. In this study, we collected tension coupon test results of LDSS and created the simple estimated equation by means of linear regression analysis. Also, we predicted the mechanical properties by using Random Forest (RF) which is one of machine learning method. According to comparison predicted results by RF with those by estimated equation, it was revealed that RF has same prediction accuracy of mechanical properties as estimation equation.