Prediction of A_f temperature for copper based shape memory alloys

Abstract

This study presents the gene expression programming (GEP) soft computing technique as a new tool for the formulation of the Austenite finish (A_f) temperature of Cu-based shape memory alloys (SMA) for various compositions and heat treatments. The objective of this study is to provide an alternative formulation to related design composition and verify the robustness of GEP for the formulation of such structural problems. The training and testing patterns of the proposed GEP formulation is based on well established experimental results from the literature. The GEP based formulation results are compared with the experimental results and found to be quite reliable.