Optimization of Fiber Reinforced Laminates for Maximum Fatigue Life using Particle Swarm Optimization

Composites are commonly used materials in many structural applications because of their advantageous like lightness or strength-to-weight ratio. With the increased use of composites it has been understood that their deformations in terms of fatigue is more complex than that of metals. Although fatigue behavior of composites has been studied extensively, little attention was paid to optimization of composites under fatigue. In this study, an improved methodology is proposed to find globally optimum designs of composite laminates subject to given in-plane loads for maximum fatigue life. For this purpose, a parametric fatigue life prediction model, proposed by Fawaz and Ellyin, was coupled with a global optimization technique, Particle Swarm Optimization (PSO), which is a meta-heuristic optimization algorithm. The number of distinct fiber orientation angles and the number of plies each lamina contains were predetermined. The fiber orientation angles in each layer were taken as design variables and determined in the design process. A number of problems were solved to demonstrate the effectiveness and reliability of the proposed method.