Machine Learning-Based Prediction of Tensile Properties in Cast Stainless Steel Influenced by Chemical Composition Variation

In the category of cast stainless steels, there are several variants per different level of addition of chromium, vanadium along with some minor elements, such as molybdenum, niobium, tungsten to meet the requirement of corrosion and oxidation resistance. However, the influence of chemical composition variations on the mechanical properties of cast SS continues to lack a clear understanding. In the present study, via machine learning, the effects of each element on the tensile properties of the selected cast stainless steel are studied. The machine learning model is then used to predict how variations in elements affect tensile behavior, with the predictions validated through physical testing.