Fatigue strength estimation of adhesively bonded tongue and groove joint of thick woven composite sandwich structures using genetic algorithm approach

In the present work, the fatigue behavior of tongue and groove joints bonded by a toughened epoxy adhesive was investigated. Axial cyclic tests were performed by different design configuration conditions and the effects of design parameters were evaluated. The bonding strength of adhesives under fatigue loading is influenced by many factors such as, the length of bondline, adhesive thickness, traverse pre-stress on near the free edges of bond line and material of the joining parts. Since all these factors affect the fatigue strength of the adhesively joined parts, the effects of these parameters need to be investigated. The present paper describes the use of the stochastic search process that is the basis of a Genetic Algorithm, in developing fatigue strength estimation of adhesively bonded thick woven E-glass/vinyl ester laminates. Non-linear estimation models were developed using genetic algorithm. Developed models are validated with experimental data. Genetic Algorithm Fatigue Strength Estimation Model for Tongue and Groove Joints was developed to estimate the fatigue strength of the adhesively bonded joint. The strongest adhesively bonded joints can be achieved by selecting optimum design parameters obtained from the models. The logarithmic number of cycles was increased 2.46 times by selecting aluminum EN AW 5083 insert instead of composite insert materials. The joint fatigue strength was significantly improved by selecting appropriate design parameter values. © 2011 Elsevier Ltd. All rights reserved