Application of Particle Swarm Optimization for Improvement of Peel Strength in a Laminated Double-Lap Composite Joint

Abstract

A double lap joint is commonly used in thin structures under low running loads. Peel and inter-laminar stresses are among the major limitations of this type of joint, which may cause delamination failure. These stresses should be determined for designing a stronger structure. This study presents a method based on particle swarm optimization to find the best layup for a classic double lap joint under horizontal constant tensile forces. The peel stress equation is analytically obtained and utilized as the objective function for the algorithm. The method’s accuracy is explored by assessing the algorithm’s ability. This helps to find the best arrangement with the highest strength delamination against considering four initial layups. The results show that the optimized layups, on average, can reduce peel stress by about 96%. Additionally, the effects of different parameters on joint strength are investigated.

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“…Parameter tuning prevents time-taking execution of algorithms and improves the reliability of obtained solutions ( Babaveisi et al, 2018 ). Among existing design of experiment (DOE) techniques, Taguchi has recorded a solid background in tuning parameters of metaheuristic algorithms, and it has extensive application in this field of research ( Arjomandi et al, 2022 , Colombaroni et al, 2020 ). The response value (Y) for the Taguchi technique is defined as Eq.…”