Parametric Optimization for Bonded Single Lap Woven GFRP Joint: A TLBO-ANOVA Approach

Abstract

The present study investigates the bond strength capability of epoxybased adhesive used for woven type Glass Fiber Reinforced Polymer (GFRP) in a Single Lap Bonded Joint (SLBJ) configuration. Cohesive Zone Modelling (CZM), encompassing a bilinear traction-separation law, is utilised to study the failure behaviour in the adhesive layer. Maximum Stress Criteria are opted for the damage initiation, and critical energy release rate is used for damage evolution and separation of the adhesive layer. Three parameters constituting overlap length, overlap width and thickness of adhesive in the joint are varied, and their response to the quasi-static tensile test is obtained in the form of shear stress and peel stress of the specimen. Teaching Learning Based Optimization (TLBO), a robust metaheuristic algorithm is implemented to investigate the design space and identify the optimal parameters to maximise the shear Strength. The analysis of variance (ANOVA)is explored in this study to determine the significance of each parameter in relation to the bond strength. The findings of this research work offer insight to the researchers seeking to enhance the performance of adhesively bonded FRP joints.