Journal
COMPOSITES SCIENCE AND TECHNOLOGY
Volume 149, Issue -, Pages 116-126Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.compscitech.2017.06.018
Keywords
Adhesive joints; Nano composites; Fatigue; Non-destructive testing; Carbon nanofibres
Categories
Funding
- Australian Research Council's Discovery Grant [DP140100778]
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In the present work we report on the use of carbon nanofibres (CNFs) to simultaneously improve the cyclic fatigue resistance and the detectability of disbonding in adhesively-bonded structures made of carbon-fibre reinforced-plastic (CFRP) composites. The effects of the concentration of the CNFs (i.e. 0.4, 0.7 and 1.0 wt%) and their orientation (i.e. random versus aligned) in the epoxy-adhesive layer between two CFRP substrates are investigated. The results show that increasing the concentration of randomly oriented CNFs (a) improves greatly the mode I fatigue resistance of the adhesive layer, including raising the crack growth threshold of the cyclic strain-energy release-rate, and (b) increases the quasi static fracture toughness. Further improvements in the fatigue resistance occur when the CNFs are aligned perpendicular to the plane of the joint, i.e. normal to the crack plane, as opposed to being, randomly-oriented in the adhesive layer. In addition, the CNFs form a conductive network that makes it possible to detect and characterise fatigue-induced disbonding using an electrical-resistance technique. A simple model is developed for the relationship between the disbond (i.e. crack size) and the electrical resistance of a bonded joint with conductive substrates. Finite element analyses are carried out to quantify the applicability of this model as a function of the conductivity of the adhesive from 10(-4) S/m to 1 S/m. The results confirm that the proposed simple model is highly accurate for joints where the composite substrates have a through-thickness electrical conductivity exceeding a hundred times that of the adhesive. This research paves the way for new multi-functional adhesives with greatly enhanced fatigue resistance and disbond detection capability. (C) 2017 Elsevier Ltd. All rights reserved.
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