Abstract

This paper presents an application of Genetic Algorithm coupled with Artificial Neural Network of laminated hybrid composite quadrilateral plate with varying stacking sequence, crack-length ratio, length-width ratio and volume of fraction to optimize the natural frequency. The plate is made with Carbon-Boron-Carbon Epoxy materials and modeled using Classical Laminated Plate Theory and evaluated all set of results considering two boundary conditions, (i) Supported to all sides (SSSS) and (ii) two sides are supported and the other two adjacent sides are clamped (CCSS) by applying the concept of Artificial Neural Networks and Genetic Algorithm to optimize the problem. Results are presented for optimization of a stacking sequence of symmetrical three-layer quadrilateral plate. This process provides the systematic and efficient approach for design optimization of the hybrid laminated composite plate.

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