Machine learning-based predictions and analyses of the creep rupture life of the Ni-based single crystal superalloy
Yanzhan Chen,
Yaohua Zhao
Abstract:The evaluation of creep rupture life is complex due to its variable formation mechanism. In this paper, machine learning algorithms are applied to explore the creep rupture life span as a function of 27 physical properties to address this issue. By training several classical machine learning models and comparing their prediction performance, XGBoost is finally selected as the predictive model for creep rupture life. Moreover, we introduce an interpretable method, Shapley additive explanations (SHAP), to explai… Show more
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