Deveci, Hamza Arda; Artem, Hatice Seçil; Güneş, Mehmet Deniz; Tanoğlu, Metin

This article introduces a design procedure to find the optimum fiber orientations of carbon/epoxy composite laminates for fatigue life advancement. The approach incorporates a fatigue failure tensor polynomial model and employs a hybrid algorithm, combining particle swarm optimization and sequential quadratic programming. Firstly, material properties of quasi-static and fatigue of the carbon/epoxy composites, fabricated by the vacuum-assisted resin transfer molding method, were determined to be used in the model. Various design problems involving two optimization scenarios were then solved using the hybrid algorithm. The algorithm’s performance was also evaluated by specific test problems, confirming its speed and robustness. The optimally fiber-oriented carbon/epoxy composite laminates having maximum fatigue lives were obtained for many critical in-plane cyclic loading cases. To validate the proposed design procedure, two optimum designs were experimentally verified under uniaxial loading conditions. The results indicated a good correlation between the estimated fatigue life of the optimally designed laminates and experimental data. This methodology offers a promising approach for the design of carbon/epoxy composite laminates with superior fatigue strength, particularly significant in specific industrial applications.

Deveci, H Arda; Artem, H 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.

Deveci, H Arda; Aydin, Levent; Seçil Artem, H.

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.