Numerical study of adhesively bonded dissimilar materials

Date

2025-9-1

Author

Öztürk, Ömer Taha

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Adhesives are used in industries such as defense and aerospace to bond various materials instead of conventional methods. The main advantages of adhesives on conventional fasteners are lower joint weight, uniform stress distribution, damping of vibration and shock, and bonding dissimilar materials. Because of these advantages, they have become a solution to different design problems in industries. Therefore, various studies have been carried out to understand behavior of adhesives and predict their failure; however, bonding different materials complicates the analysis of adhesively bonded joints. This thesis aims to investigate different material models numerically for an adhesive used in single-lap joints with dissimilar adherends and to compare the results. Araldite 2015, a ductile epoxy-based adhesive, is used as the bonding material in single-lap joints formed by three different adherends that are 304 stainless steel, 7075-O aluminum alloy, and carbon fiber reinforced polymer. Piecewise hardening with von-Mises yield criterion, piecewise hardening with Drucker-Prager yield criterion, Johnson-Cook hardening with von-Mises yield criterion, and Ogden hyperelastic models for the adhesive are employed as material models. The Cohesive Zone Model, built into the finite element software, and ductile fracture criteria, implemented via user subroutines, are used to predict the failure of adhesively bonded joints. Furthermore, this thesis proposes a modified version of the Ayada ductile fracture criterion and a combined numerical model that uses an elastoplastic layer with two cohesive layers for the adhesive. The comparison of the results reveals that the modified Ayada ductile fracture criterion leads to considerable improvement in failure prediction.

Subject Keywords

Adhesive, Cohesive zone model, Ductile fracture, Plasticity

URI

https://hdl.handle.net/11511/115642

Collections

Graduate School of Natural and Applied Sciences, Thesis