Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9171
Title: On the estimation and optimization capabilities of the fatigue life prediction models in composite laminates
Authors: Deveci, Hamza Arda
Artem, Hatice Seçil
Keywords: Composite laminates
Multiaxial fatigue
Life prediction
Optimization
Hybrid algorithm
Publisher: SAGE Publications
Abstract: In this study, the estimation and optimization capabilities of the multiaxial fatigue life prediction models, namely, Failure Tensor Polynomial in Fatigue, Fawaz-Ellyin, Sims-Brogdon and Shokrieh-Taheri are investigated comparatively. Fatigue life predictions are obtained for multidirectional graphite/epoxy, glass/epoxy, carbon/epoxy and carbon/PEEK composite laminate data taken from the literature. The prediction study shows that the models can predict the fatigue behavior of the multidirectional laminates at different degrees of proximity. In the optimization, a hybrid algorithm combining particle swarm algorithm and generalized pattern search algorithm is used to search the optimum stacking sequence designs of the laminated composites for maximum fatigue life. The hybrid algorithm shows superior performance in terms of computational time and finding improved global optima compared to the best results presented in the literature. After the capability of the models and the reliability of the algorithm are revealed, several lay-up design problems involving different cyclic loading scenarios are solved. The results indicate that the reliability of the optimization may considerably change according to the used model even if the model may yield reasonable prediction results.
URI: https://doi.org/10.1177/0731684418791231
https://hdl.handle.net/11147/9171
ISSN: 0731-6844
1530-7964
Appears in Collections:Mechanical Engineering / Makina Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
0731684418791231.pdf624.49 kBAdobe PDFView/Open
Show full item record



CORE Recommender

SCOPUSTM   
Citations

7
checked on Mar 22, 2024

WEB OF SCIENCETM
Citations

7
checked on Mar 27, 2024

Page view(s)

90
checked on Mar 25, 2024

Download(s)

50
checked on Mar 25, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.