Design of Metals and Alloys with High Spall Strengths

Dynamic tensile failure, or spall failure, is an important property for understanding a material's response to high-strain-rate deformation and shock-wave compression. Spall strength measurements have been performed on many metals and alloys, however, there exists no correlation between mechanical properties and spall strengths of this broad category of materials that would enable predictive capability. We have employed data analytic techniques to examine and tabulate the measured spall strength values for a number of metals and alloys from literature. The spall strength values are correlated with other, more easily accessible mechanical properties such as yield and tensile strengths and elastic moduli – referred to as "proxy properties," using machine learning. The correlations are then used to build a random forest model. The model provides a predictive classification of high, medium, or low spall strength values of metals and alloys for which there is no experimental data available. These design guidelines will aid the search for materials with high tolerance to spall failure at high strain rates.