Optimum Design of Fatigue-Resistant Composite Laminates Using Hybrid Algorithm

Loading...

Date

Authors

Artem, Hatice Seçil

Journal Title

Journal ISSN

Volume Title

Publisher

Open Access Color

BRONZE

Green Open Access

Yes

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Top 10%
Influence
Average
Popularity
Top 10%

relationships.isProjectOf

relationships.isJournalIssueOf

Abstract

In this study, a fatigue life prediction model termed as Failure Tensor Polynomial in Fatigue (FTPF) is applied to the optimum stacking sequence design of laminated composites under various in-plane cyclic loadings to obtain maximum fatigue life. The validity of the model is investigated with an experimental correlation using the data available in the literature. The correlation study indicates the reliability of FTPF, and its applicability to different composite materials and multidirectional laminates. In the optimization, a hybrid algorithm combining genetic algorithm and generalized pattern search algorithm is used. It is found by test problems that the hybrid algorithm shows superior performance in finding global optima compared to the so far best results in the literature. After the verifications, a number of problems including different design cases are solved, and the optimum designs constituted of discrete fiber angles which give the maximum possible fatigue lives are proposed to discuss. A comparison study is also performed with selected design cases to demonstrate potential advantages of using non-conventional fiber angles in design.

Description

Keywords

Fatigue, Hybrid algorithm, Laminated composites, Life prediction, Optimization, Optimization, Hybrid algorithm, Life prediction, Fatigue, Laminated composites

Fields of Science

0203 mechanical engineering, 02 engineering and technology

Citation

Deveci, H. A., and Artem, H. S. (2017). Optimum design of fatigue-resistant composite laminates using hybrid algorithm. Composite Structures, 168, 178-188. doi:10.1016/j.compstruct.2017.01.064

WoS Q

Scopus Q

OpenCitations Logo
OpenCitations Citation Count
20

Volume

168

Issue

Start Page

178

End Page

188
PlumX Metrics
Citations

CrossRef : 7

Scopus : 22

Captures

Mendeley Readers : 24

SCOPUS™ Citations

22

checked on May 01, 2026

Web of Science™ Citations

16

checked on May 01, 2026

Page Views

583

checked on May 01, 2026

Downloads

541

checked on May 01, 2026

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
2.51510055

Sustainable Development Goals

SDG data is not available