Artificial neural network combined with damage parameters to predict fretting fatigue crack initiation lifetime-Reference-Cited by-同舟云学术

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Artificial neural network combined with damage parameters to predict fretting fatigue crack initiation lifetime

Published:2022-11 Issue: Volume:175 Page:107854
ISSN:0301-679X
Container-title:Tribology International
language:en
Short-container-title:Tribology International

Author:

Wang Can,Li Yifei,Tran Ngoc Hoa,Wang Dagang,Khatir Samir,Wahab Magd Abdel

Publisher

Elsevier BV

Subject

Surfaces, Coatings and Films,Surfaces and Interfaces,Mechanical Engineering,Mechanics of Materials

Reference43 articles.

1. Recent developments in the understanding of fretting fatigue;Nowell;Eng Fract Mech,2006

2. Investigations on the fretting fatigue failure mechanism of bolted joints in high strength steel subjected to different levels of pre-tension;Jiménez-Peña;Tribology Int,2017

3. Fretting fatigue in dovetail blade roots: experiment and analysis;Rajasekaran;Tribol Int,2006

4. Fundamental investigations of fretting fatigue: part 4, the effect of mean stress;Nishioka;Bull JSME,1969

5. Crack initiation and propagation under fretting fatigue of inconel 600 alloy;Jeung;J Mech Sci Technol,2015

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1. Nonlocal multiaxial fatigue model based on artificial neural networks for predicting fretting fatigue life of dovetail joints;International Journal of Fatigue;2024-12

2. A simple linear regression strategy for fretting fatigue life estimates;Tribology International;2024-10

3. Crack propagation simulation and overload fatigue life prediction via enhanced physics-informed neural networks;International Journal of Fatigue;2024-09

4. Prediction of fretting fatigue lifetime of aluminium alloy treated with Friction Stir Processing using continuum damage mechanics;Tribology International;2024-07

5. Effect of shot peening parameters on fretting fatigue lifetime;Tribology International;2024-05

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