Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    Citation - Scopus: 13
    Optimum Design of Anti-Buckling Behavior of Graphite/Epoxy Laminated Composites by Differential Evolution and Simulated Annealing Method
    (MIM RESEARCH GROUP, 2019) Akçair,M.; Savran,M.; Aydın,L.; Ayakdaş,O.; Öztürk,S.; Küçükdoğan,N.
    Stacking sequence design and optimization of 64 layered symmetric-balance graphite/epoxy laminated composite have been performed. The optimization problems aim to find the optimum stacking sequence maximizing the critical buckling load by single objective optimization approach. Differential Evolution (DE) and Simulated Annealing (SA) optimization algorithms are proposed to solve the problems. The effect of the aspect ratios (a/b) and in-plane biaxial compressive loading ratios (Nx/Ny) on critical buckling load are investigated. In order to see the effect of discrete increments of fiber orientation angle on critical buckling load, 1°, 5°, 15°, 30° and 45° fiber angle increments are also considered. The results show that (i) the proposed algorithms DE and SA exhibit comparable performance in terms of critical buckling load when compared Genetic algorithm (GA) and Generalized pattern search algorithm (GPSA), (ii) DE and SA find distinct stacking sequence configurations in terms of buckling load for the same laminated structure design problems. © 2019 MIM Research Group. All rights reserved.
  • Article
    Citation - WoS: 19
    Citation - Scopus: 19
    Comparison of Stochastic Search Optimization Algorithms for the Laminated Composites Under Mechanical and Hygrothermal Loadings
    (SAGE Publications Inc., 2011) Aydın, Levent; Artem, Hatice Seçil
    The aim of the present study is to design the stacking sequence of the laminated composites that have low coefficient of thermal expansion and high elastic moduli. In design process, multi-objective genetic algorithm optimization of the carbon fiber laminated composite plates is verified by single objective optimization approach using three different stochastic optimization methods: genetic algorithm, generalized pattern search, and simulated annealing. However, both the multi- and single-objective approaches to laminate optimization have been used by considerably few authors. Simplified micromechanics equations, classical lamination theory, and MATLAB Symbolic Math toolbox are used to obtain the fitness functions of the optimization problems. Stress distributions of the optimized composites are presented through the thickness of the laminates subjected to mechanical, thermal, and hygral loadings.