What question did this study set out to answer?

To determine the optimal design variables that maximize the buckling load of variable-stiffness composite laminates.

February 26, 20260 citations

逐次近似最適化による曲線繊維強化複合材の座屈荷重最適化

Key Points

To determine the optimal design variables that maximize the buckling load of variable-stiffness composite laminates.
Applied sequential approximate optimization using artificial neural networks (ANN).
Analyzed buckling behavior with finite element analysis (FEA).
Modeled the relationship between design variables and buckling load.
Optimized curvilinear fibers enhanced buckling resistance significantly.

Abstract

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.

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Cite This Study

Wang et al. (Wed,) studied this question.

synapsesocial.com/papers/699f95a81bc9fecf3dab3ada https://doi.org/https://doi.org/10.1299/jsmedmc.2025.3

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