APPLICATION OF HYBRID MULTI-OBJECTIVE GRAVITATIONAL SEARCH ALGORITHM FOR PROCESS OPTIMIZATION OF CARBON FIBRE-REINFORCED POLYMER

Abstract

This research explores the optimization of carbon fibre-reinforced plastic (CFRP) laminates for aerospace applications, specifically targeting the skin of a medium-format fighter aircraft. The study focuses on modifying the original equipment manufacturer (OEM) general-purpose curing cycle to enhance the mechanical properties of CFRP laminates. Through experimental work, an optimized curing cycle is developed, resulting in superior tensile strength, impact toughness, and hardness of the CFRP laminate. Initially, a single objective Gravitational Search Algorithm (GSA) is employed to validate individual optimum properties of the CFRP laminate. Subsequently, an indigenous Hybrid Multi-objective GSA (HMOGSA) is devised and utilized to validate the experimental results comprehensively. Moreover, to authenticate the findings of the developed HMOGSA, the experimental results are cross-validated using a multi-objective Genetic Algorithm (MOGA). The research findings highlight the efficacy of the proposed HMOGSA approach in optimizing CFRP laminates for aerospace applications. This stud contributes to advancing the understanding and practical implication of optimizing techniques in the design and fabrication of high performance composite materials for aerospace engineering.