A generalized ANN-multiaxial fatigue nonlocal approach to compute fretting fatigue life for aeronautical Al alloys

This work presents two new models, based on the use of Artificial Neural Networks (ANN) and non-local stress parameters physically related to crack initiation processes, to estimate fretting fatigue (FF) life. To train and validate these models, several FF data for different aeronautical Al alloys a...

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Bibliographic Details
Published inTribology international Vol. 180; p. 108250
Main Authors Brito Oliveira, Giorgio André, Cardoso, Raphael Araújo, Freire Júnior, Raimundo Carlos Silverio, Araújo, José Alexander
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.02.2023
Subjects
Aluminum alloys
Artificial neural networks
Fretting fatigue
Multiaxial fatigue
Aluminum alloys
Multiaxial fatigue
Fretting fatigue
Artificial neural networks
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Summary:This work presents two new models, based on the use of Artificial Neural Networks (ANN) and non-local stress parameters physically related to crack initiation processes, to estimate fretting fatigue (FF) life. To train and validate these models, several FF data for different aeronautical Al alloys are gathered in the literature. To test the accuracy and generalization capability of the models, data related to two Al alloys not considered in the training phase are employed and life estimates are compared with those computed according to two well-established multiaxial fatigue models. The ANN models provide more accurate estimates than those provided by the fatigue models examined, as well as showed a good generalization capability, which suggests their potential for future industrial applications.
ISSN:0301-679X
1879-2464
DOI:10.1016/j.triboint.2023.108250