Fatigue life prediction of aluminum alloy via knowledge-based machine learning
Author:
Publisher
Elsevier BV
Subject
Industrial and Manufacturing Engineering,Mechanical Engineering,Mechanics of Materials,General Materials Science,Modeling and Simulation
Reference38 articles.
1. Fatigue behavior of 2618–T851 aluminum alloy under uniaxial and multiaxial loadings;Malek;Int J Fatigue,2020
2. Fatigue behavior of high-entropy alloys: A review;Chen;Sci China Technol Sci,2018
3. The exponential law of endurance tests;Basquin;Proc Am Soc Test Mater,1910
4. Application of bi-linear log–log S-N model to strain-controlled fatigue data of aluminum alloys and its effect on life predictions;Fatemi;Int J Fatigue,2005
5. A probabilistic Stüssi function for modelling the S-N curves and its application on specimens made of steel S355J2+N;Toasa Caiza;Int J Fatigue,2018
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