Mechanical Engineering / Makina Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/4129

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Author: search.filters.author.Deveci, Hamza Arda

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Now showing 1 - 5 of 5
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Fatigue Life Prediction and Optimization of Gfrp Composites Based on Failure Tensor Polynomial in Fatigue Model With Exponential Fitting Approach
    (SAGE Publications, 2022) Güneş, Mehmet Deniz; İmamoğlu Karabaş, Neslişah; Deveci, Hamza Arda; Tanoğlu, Gamze; Tanoğlu, Metin
    In this study, a new fatigue life prediction and optimization strategy utilizing the Failure Tensor Polynomial in Fatigue (FTPF) model with exponential fitting and numerical bisection method for fiber reinforced polymer composites has been proposed. Within the experimental stage, glass/epoxy composite laminates with (Formula presented.), (Formula presented.), and (Formula presented.) lay-up configurations were fabricated, quasi-static and fatigue mechanical behavior of GFRP composites was characterized to be used in the FTPF model. The prediction capability of the FTPF model was tested based on the experimental data obtained for multidirectional laminates of various composite materials. Fatigue life prediction results of the glass/epoxy laminates were found to be better as compared to those for the linear fitting predictions. The results also indicated that the approach with exponential fitting provides better fatigue life predictions as compared to those obtained by linear fitting, especially for glass/epoxy laminates. Moreover, an optimization study using the proposed methodology for fatigue life advancement of the glass/epoxy laminates was performed by a powerful hybrid algorithm, PSA/GPSA. So, two optimization scenarios including various loading configurations were considered. The optimization results exhibited that the optimized stacking sequences having maximized fatigue life can be obtained in various loading cases. It was also revealed that the tension-compression loading and the loadings involving shear loads are critical for fatigue, and further improvement in fatigue life may be achieved by designing only symmetric lay-ups instead of symmetric-balanced and diversification of fiber angles to be used in the optimization.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 5
    Single- and Multiobjective Optimizations of Dimensionally Stable Composites Using Genetic Algorithms
    (Springer, 2021) Aydın, Levent; Artem, Hatice Seçil; Deveci, Hamza Arda
    The present study aims to design stacking sequences of dimensionally stable symmetric balanced laminated carbon/epoxy composites, with different numbers of layers, with a low coefficient of thermal expansion and high elastic moduli. To avoid excessive interlaminar stresses in the composites, the contiguity constraint for plies is also taken into consideration. In the design process, both single- and multiobjective optimization approaches, including genetic algorithms, are utilized. Results showed that stacking sequences ensuring lower thermal expansion coefficients and higher elastic moduli than those of traditional laminate designs can be obtained.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 10
    On the Estimation and Optimization Capabilities of the Fatigue Life Prediction Models in Composite Laminates
    (SAGE Publications, 2018) Deveci, Hamza Arda; Artem, Hatice Seçil
    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.
  • Article
    Citation - WoS: 16
    Citation - Scopus: 22
    Optimum Design of Fatigue-Resistant Composite Laminates Using Hybrid Algorithm
    (Elsevier Ltd., 2017) Deveci, Hamza Arda; Artem, Hatice Seçil
    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.
  • Article
    Citation - WoS: 32
    Citation - Scopus: 38
    Buckling Optimization of Composite Laminates Using a Hybrid Algorithm Under Puck Failure Criterion Constraint
    (SAGE Publications Inc., 2016) Deveci, Hamza Arda; Aydın, Levent; Artem, Hatice Seçil
    In this study, an optimization procedure is proposed to find the optimum stacking sequence designs of laminated composite plates in different fiber angle domains for maximum buckling resistance. A hybrid algorithm combining genetic algorithm and trust region reflective algorithm is used in the optimization to obtain higher performance and improve the quality of solutions. As a novelty, Puck fiber and inter-fiber failure criteria are directly implemented to the optimization problems as nonlinear function constraints, which have allowed more consistent and feasible results. The performance of the hybrid algorithm is demonstrated by comparing with the individual performances of genetic and trust region reflective algorithms via test problems from the literature. Also, a study is performed to exhibit the effectiveness of the selected failure criterion as constraint among the other common criteria. The proposed procedure is used to solve many problems including various design considerations. The results indicate that reliable stacking sequence designs can be achieved in specific configurations even for the composite plates subjected to superior buckling loads when Puck physically based (3D) failure theory is considered as a first ply failure constraint in the buckling optimization.