Physics‐Embedded Machine Learning for Fatigue Cumulative Damage Prediction

ABSTRACT Fatigue damage accumulation is critical to the safety and reliability of mechanical structures, yet accurate prediction remains challenging, especially under small‐sample conditions. This study proposes an innovative physics‐embedded machine learning (ML) framework to enhance residual fatig...

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Bibliographic Details

Published in:	Fatigue & fracture of engineering materials & structures Vol. 48; no. 10; pp. 4352 - 4374
Main Authors:	Gao, Zhiyuan, Jiang, Xiaomo, Guo, Yifan, Cui, Mingqing, Wang, Shengbo
Format:	Journal Article
Language:	English
Published:	Oxford Wiley Subscription Services, Inc 01.10.2025
Subjects:	Cumulative damage Damage accumulation damage equivalence fatigue cumulative damage Fatigue failure Machine learning physics‐embedded machine learning small‐sample prediction two‐level loading
ISSN:	8756-758X, 1460-2695
Online Access:	Get full text
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