Application of GA Optimization in Analysis of Variable Stiffness Composites
Abstract:Variable angle tow describes the fibres which are
curvilinearly steered in a composite lamina. Significantly, stiffness
tailoring freedom of VAT composite laminate can be enlarged and
enabled. Composite structures with curvilinear fibres have been
shown to improve the buckling load carrying capability in contrast
with the straight laminate composites. However, the optimal design
and analysis of VAT are faced with high computational efforts
due to the increasing number of variables. In this article, an
efficient optimum solution has been used in combination with 1D
Carrera’s Unified Formulation (CUF) to investigate the optimum fibre
orientation angles for buckling analysis. The particular emphasis is
on the LE-based CUF models, which provide a Lagrange Expansions
to address a layerwise description of the problem unknowns.
The first critical buckling load has been considered under simply
supported boundary conditions. Special attention is lead to the
sensitivity of buckling load corresponding to the fibre orientation
angle in comparison with the results which obtain through the
Genetic Algorithm (GA) optimization frame and then Artificial
Neural Network (ANN) is applied to investigate the accuracy of
the optimized model. As a result, numerical CUF approach with
an optimal solution demonstrates the robustness and computational
efficiency of proposed optimum methodology.
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