Development and assessment of machine learning models for predicting fatigue response in AA2024

Development and assessment of machine learning models for predicting fatigue response in AA2024

Accurate prediction of fatigue life is vital in the design of aerospace components subjected to varying stress levels and loading frequencies. In the current research, machine learning (ML) models were developed to predict the fatigue life of AA2024-T6, a popular aerospace grade alloy, under differe...

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Bibliographic Details
Main Authors: Jagadesh Kumar Jatavallabhula, Tshepo Gaonnwe, Sibusiso Nginda, Vasudeva Rao Veeredhi
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Materials Research Express
Subjects:
aerospace
fatigue
machine learning
ELNET
k-NN
random forest
Online Access:https://doi.org/10.1088/2053-1591/ada41c
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