Revisiting the Copson Curve Using Data Science

This work applies machine learning to holistically interrogate the influence of metallurgical factors, such as chemical composition, heat treatment, and mechanical properties, on the stress corrosion cracking resistance of corrosion-resistant alloys. In particular, we explored the effect of nickel in reducing the stress corrosion cracking susceptibility in boiling magnesium chloride, arguably a controversial topic since Copson’s 1959 seminal publication. This paper offers insights into the synergies of nickel with other alloying elements that ultimately impact the resistance to stress corrosion cracking. Furthermore, a more detailed description of statistical patterns in the so-called Copson curve is provided.