Investigation of fatigue crack propagation in adhesively bonded joints using fatigue testing, finite element analysis and neural networks

Abstract

The current paper presents research aiming at characterizing the fatigue behaviour of adhesively bonded joints. In this study, a new mathematical model to predict fatigue crack propagation rates for adhesively bonded joints has been investigated and presented. The proposed method uses fatigue test data and stiffness data obtained from finite element model of bonded joints. T-peel and single lap shear bonded joints were prepared using aluminium alloy AA5754 and Betamate epoxy adhesive 4601. The fatigue tests were conducted using constant amplitude loading using an R ratio of 0.1 at a frequency of 10 Hz. The FE models used in this work were developed using fracture mechanics tools in Abaqus. The results were post processed to extract energy release rates in form of J Integrals and stress intensity factors. The stiffness results obtained from both experimental testing and numerical studies were combined using appropriate curve fitting models proposed in the literature to estimate the fatigue crack propagation rates and obtained the de-bond curves in the Paris regime for such joints. The crack growth rates were further modelled and validated using neural network technique in MATLAB.