Prediction of notch strength ratio of a notched tensile ductile iron using multiple linear regression model

This study aims to create a model by examining the effect of the matrix structure and notch root radius on the notch strength ratio (NSR) in an alloyed ductile cast iron through multiple linear regression analysis. For this purpose, several heat treatments were applied to obtain ferritic, pearlitic/ferritic, pearlitic, tempered martensitic, lower bainitic, and upper bainitic matrix structures in cast iron. Hardness and tensile tests were applied to determine the hardness and 0.2 yield strength of matrix structures, which were then considered independent variables in the regression analysis. Additionally, tensile tests were conducted on circumferentially V-notched samples with a notch root radius range of 0.05-0.8 mm, and the notch radius was used as the third independent variable in the analysis. A model was developed by multiple regression to predict the NSR with the aid of the hardness, 0.2 yield strength, and notch radius independent variables. The analysis had an adjusted R2 value of 0.886, which explains that 88.6 % of predicted NSR values can be varied by the hardness, 0.2 yield strength, and notch root radius. The model predicted satisfactory NSR values in matrix structures, exhibiting only minimal residuals.