Abstract
A Gaussian process regression model for estimating the creep rupture stress of single crystal nickel-based superalloys is constructed. It is built and validated on data disclosed in patents as well as scientific and technical reports. This model is coupled with computational thermodynamics for the prediction of microstructural features, and a model for the estimation of density. Using this combination, the key characteristics of a large number of potential alloys are systematically computed as a function of their composition. Materials specifications targeted towards applications as turbine blades, which none of the alloys from the creep database follow, narrow down the search from 300 000 000 to 180 000 alloys. A large number of these candidates are predicted as featuring greater specific properties than existing single crystal nickel-based superalloys. The selection criteria used to isolate alloys for experimental validation are discussed, and lead to several alloys displaying good agreement between their predicted microstructure and estimated properties.
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