On the use of data-driven machine learning for remaining life estimation of metallic materials based on Ye-Wang damage theory-Reference-Cited by-同舟云学术

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On the use of data-driven machine learning for remaining life estimation of metallic materials based on Ye-Wang damage theory

Published:2022-03 Issue: Volume:156 Page:106666
ISSN:0142-1123
Container-title:International Journal of Fatigue
language:en
Short-container-title:International Journal of Fatigue

Author:

Gan Lei,Wu Hao,Zhong Zheng

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Mechanics of Materials,General Materials Science,Modeling and Simulation

Reference68 articles.

1. Nonlinear fatigue damage accumulation: Isodamage curve-based model and life prediction aspects;Zhu;Int J Fatigue,2019

2. Application of damage concepts to predict creep-fatigue failures;Lemaitre;J Eng Mater Technol,1979

3. Fatigue life prediction under variable loading based on a new non-linear continuum damage mechanics model;Dattoma;Int J Fatigue,2006

4. Parametric probabilistic approach for cumulative fatigue damage using double linear damage rule considering limited data;Dias;Int J Fatigue,2019

5. A probabilistic interpretation of the Miner number for fatigue life prediction;Fernández-Canteli;Frat ed Integrita Strutt,2014

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