Experimental Validation of Property Models and Databases for Computational Superalloy Design

Abstract

Computational superalloy development is a powerful alternative to the conventional experimental approach. Based on thermodynamic databases and the CALPHAD method, it is possible to estimate the properties of a large number of potential alloys and select the most promising ones. However, the accuracy of the databases and complementary property models can be unsatisfying. The accuracy of two mass density and lattice parameter models and the TTNI8 and TCNI10 databases is analyzed in detail on the experimental basis of computationally optimized single‐crystalline superalloys. Various properties are measured and compared to the results of the property models and databases. Neither of the databases is superior to the other and especially the solvus temperature is not accurately described in both. The new mass density model, a linear regression based on the molar mass, is more reliable for low‐density alloys. Both lattice parameter model versions slightly overestimate the room‐temperature  lattice parameter. The lattice parameter, however, is more accurately calculated using the new model version. The results of this study can be readily used to improve a multicriteria alloy optimization tool for computational superalloy design.