Evaluation of fatigue damage in adhesive bonding: Part 1: Bulk adhesive - Wahab, Magd Abdel; Hilmy, Irfan; Ashcroft, Ian Anthony; Crocombe, Andrew David (Taylor and Francis, 2010)
The measurement of fatigue damage in adhesive bonding has been investigated. Bulk adhesive was used in this study for two reasons: the stress distribution of adhesives in bulk is simpler to investigate than adhesives in joints; and the specimen dimensions met fatigue test standards. Bulk adhesive was made from a film type of epoxy resin. In general, the characteristics and the behaviour of bulk adhesive may differ from adhesive in joint because of the presence of voids and the constraints imposed by the substrates. Low cycle fatigue tests with a load amplitude ratio of 0.1 at a frequency of 5 Hz were performed to determine the damage as a function of the number of cycles. Damage curves, i.e., the evolution of the damage variable as a function of number of cycles, were derived and plotted using an isotropic damage equation. Damage was evaluated using the decrease of stress range during the lifecycles of a constant displacement amplitude test. It was found that the damage curves were well fitted by a low cycle, fatigue damage evolution law equation. This equation was derived from a dissipation potential function. Curve fitting was performed using the robust least square technique rather than ordinary linear least square technique because damage curves have extreme points (usually near the failure point). It was found that the fitting process would not converge for adhesive fractures at high cycle values (Nf > 9000). Two damage constants A and ¥â were found from the fitting process. Each fatigue set of data, at a certain level of von-Mises stress range for the undamaged state or at the stabilized hardened state, (¥ò . eq), had a different set of damage parameters A and ¥â. Linear regression of these points was used to express A and ¥â as a function of ¥ò . eq. Using these expressions, damage curves for different levels of ¥ò . eq could be predicted.