Rubber fatigue life prediction using a random forest method and nonlinear cumulative fatigue damage model

ABSTRACT In this study, a random forest machine‐learning method is introduced on the basis of the analysis of measured constant amplitude stress fatigue data. This method aims to predict rubber fatigue life under constant amplitude stress. Strain mean value, strain amplitude, and strain ratio are us...

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Bibliographic Details
Published in:Journal of applied polymer science 2020-04, Vol.137 (14), p.n/a
Main Authors: Liu, Qiaobin, Shi, Wenku, Chen, Zhiyong
Format: Article
Language:English
Subjects:
Amplitudes
Damage assessment
Fatigue failure
Fatigue life
Independent variables
Life prediction
Materials science
Mathematical models
nonlinear cumulative fatigue damage model
Polymers
random forest
Rubber
rubber fatigue
Strain
variable amplitude stress
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Summary:ABSTRACT In this study, a random forest machine‐learning method is introduced on the basis of the analysis of measured constant amplitude stress fatigue data. This method aims to predict rubber fatigue life under constant amplitude stress. Strain mean value, strain amplitude, and strain ratio are used as independent variables, and the prediction model of rubber fatigue life under constant amplitude stress is established. A nonlinear cumulative fatigue damage model is proposed to calculate rubber fatigue life under the variable amplitude stress. Results show that the random forest method has high precision and generalization capability for rubber fatigue life prediction under constant amplitude stress and the nonlinear cumulative fatigue damage model could be employed to calculate the fatigue life of rubber under variable amplitude stress with enough accuracy according to the constant amplitude stress fatigue life data. This research can provide a reference for rubber fatigue life prediction. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020, 137, 48519.
ISSN:0021-8995
1097-4628
DOI:10.1002/app.48519