Assessment of Composite Aluminum Adhesive Joints Using Digital Image Correlation

Abstract

Traditional nondestructive evaluation (NDE) methods present significant challenges to detecting and characterizing kissing or weak bonds in adhesively bonded structures. These kissing or weak bonds also cannot transmit shear stresses or handle complex loading modes and, if not detected, can present a significant threat to the structural integrity of the components or systems. This paper demonstrates the digital image correlation (DIC) technique for evaluating adhesively bonded dissimilar materials joints subjected to kissing or weak bonds. The study employed four adhesively bonded carbon fiber reinforced plastics and aluminum (CFRP-Al) lap-shear test coupons with varied bond quality (i.e., with no contamination and three simulated kissing bond defects). The novelty of the approach presented in this paper was that this technique could detect and demonstrate changes in the normal strain (εyy) contour map of the contaminated specimens at relatively lower load levels. This load level corresponds to 15% of the failure load for the silicone and hydraulic oil contaminated sample and around 30% for the polyvinyl alcohol (PVA) contaminated sample. In addition, higher compressive strains along the overlap edges were observed in the strain map for the single lap joints due to the higher peeling stresses of the adherend and the stress concentration at the edges of an adhesively bonded joint.