This study proposes a sequential approximate optimization method using artificial neural networks (ANN) to maximize the buckling load of variable-stiffness composite laminates. Buckling behavior is analyzed via FEA, and ANN models the relationship between design variables and buckling load. Results show optimized curvilinear fibers significantly improve buckling resistance.
Wang et al. (Wed,) studied this question.