Buckling Optimization of Composite Laminates Using a Hybrid Algorithm Under Puck Failure Criterion Constraint

Abstract

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.