Data-based property prediction for single crystal superalloys (T02*)

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The objective of the project is to develop physical-based creep indicators based on composition, temperature and strain and to define them as parameters of a new property model for superalloys. Physical material parameters and mechanisms, such as gamma / gamma'-volume fractions, solid solution hardening and the kinetics of microstructure evolution, are individually evaluated with regard to their influence on the creep behaviour of the alloys. Methodically, a combination of regression analysis, data mining and machine learning methods is applied.