thick composite sandwich structures using genetic algorithm approach

The bonding strength of adhesive joints is influenced by many factors such as, the overlap, the bondline thickness, the pre-stress near the free edges of bondline, the material of the joining parts, etc. Since all these factors affect the strength of the adhesively joined parts, the effects of these parameters need to be investigated. The present paper describes the use of a stochastic search process that is the basis of genetic algorithm (GA), in developing tensile strength estimation of adhesively bonded thick woven E-glass/vinyl ester laminates. Non-linear estimation models were developed using GA. The developed models were validated with experimental data. A genetic algorithm tensile strength estimation model (GATSEM) was developed to estimate the strength of adhesively bonded tongue and groove joints. Steel S235JR insert materials and aluminum 5083 insert materials increased the joint strength by 1.7 and 1.2 times, respectively, compared to composite insert materials. There is a 2.0 times increment in the joint strength by applying a pre-stress at the edge of the tongue and groove geometry. The joint strength can be significantly improved by selecting appropriate design parameter values. (C) 2010 Elsevier Ltd. All rights reserved