Abstract
In the present work, the thermomechanical fatigue behavior and life prediction of PM superalloy under various mechanical strain amplitudes and phase angles are investigated. Results demonstrate that the thermomechanical fatigue life is phase angle dependent and the tensile mean temperature is the main factor affecting the TMF life of alternative phase angle. A modified energy-based life prediction model is proposed by considering the effects of phase angle and tensile mean temperature. Moreover, machine learning methods were used for life prediction, and the TMF lifetime at various phase angles was predicted by combining it with RF regression and modified energy model.
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