This study uses the acoustic emission structural health monitoring method to identify fracture mechanisms in composite bonded joints when varying the substrate stacking sequence. Quasi-static mode I loading tests were performed on secondary adhesively bonded multidirectional composite substrates (0, 90, 45, −45, 60 and −60° fibre orientations). An unsupervised artificial neural network combined with the visual fracture evaluation of the specimens and the Morlet continuous wavelet transform was used to cluster and give the acoustic emission signals a physical meaning. Different fracture mechanisms could be identified within the adhesive layer (i.e., cohesive failure) and in the composite substrates, including non-visible damage mechanisms (matrix micro-cracking, fibre/matrix debonding, fibre pull-out and fibre breakage). Using the Morlet continuous wavelet transform, it was possible to recognise that the highest peak frequency does not always represent the most relevant signature of the fracture mechanism. Moreover, multiple peak frequencies can be associated with multiple fracture mechanisms, such as the fibre pull-out that occurs in the combination of matrix cracking and fibre breakage. Furthermore, no differences were observed in mode I loading conditions between the acoustic emission signatures from the cohesive failure in the adhesive layer and the matrix cracking within the composite substrate. The findings of this study present a great opportunity to gain more insight into the fracture behaviour of polymer materials and fibre-reinforced polymer materials and to improve the quality of adhesively bonded joints.@en

Aiming to increase damage tolerance of adhesively bonded joints, this work explores the influence of CFRP layup of the adherends on the crack onset and crack propagation of composite bonded joints under mode I loading. Quasi-static Double Cantilever Beam tests were performed using four different CFRP layups bonded with two adhesives. Parallel to the experimental program, finite element analyses were performed to aid in understanding and identifying the various damage mechanisms in each specimen type. The results show that the CFRP layup and adhesive fracture toughness significantly influence the joint fracture phenomena at crack onset and further crack propagation. An enhancement of the joint's mode I fracture toughness values at crack onset was observed in the specimens where a crack competition between the propagation within the bondline and the composite's layers was triggered. During crack propagation, the fracture toughness of the joint increases at crack deflections between the different plies of the CFRP layup until reaching the 0° ply, where sudden delamination occurs. It has been shown that CFRP layup tailoring is a promising toughening method that, when carefully designed, has the potential to increase the maximum effective fracture toughness up to 100% when compared to pure cohesive failure.@en

Delamination growth in fibre reinforced polymer composites is generally evaluated with experiments that have been standardized for quasi-static load conditions. These tests characterize unidirectional delamination growth in mode I (DCB), mode II (ELS or ENF) of mixed mode conditions (MMB). However, little attention is paid in literature to the applicability of these tests to in-service delamination problems that are generally characterized by planar delamination growth. In this study, the relation between planar delamination growth, induced by transverse quasi-static indentation loading, and these unidirectional delamination tests was investigated. To that aim, prior planar delamination growth tests reported in literature, performed at EPFL, were analysed to identify up to what extent this planar growth could be correlated to the concepts of strain energy release and strain energy density. Once this appeared to successful, an experimental setup was designed to measure the delamination boundary during the transverse indentation loading of planar delamination specimens made of nontransparent carbon fibre reinforced polymer composites. With that set-up, quasi-static and fatigue planar delamination growth experiments were performed, and delamination contours could be successfully captured. While the quasi-static tests revealed limited growth, evaluation with numerical simulations revealed that the indentation force required to extend the delamination quasi-statically would cause damage to the specimen. This is attributed to the increasing length of the delamination contour when delaminations expand, which is not the case with standard unidirectional specimen. With the fatigue tests, however, delamination growth was achieved, but interestingly enough two phases were observed; first the delamination propagated in a planar fashion, while at some point in time work did not exceed an apparent threshold. Instead of no growth, however, the delamination still increased but then in a transverse manner. What makes this study of particular interest, is that the strain energy density as criterion could capture the strain energy offered (work) along the entire delamination contour, while the strain energy release rate described the resistance to delamination growth. This latter observation is in agreement with the original concept employed by Griffith when he formulated the basis of linear elastic fracture mechanics. This presentation present the experiments performed, the analysis of results, and will conclude with a proposal how to relate standard unidirectional tests to planar growth, considering that these standard tests contain little to no information on transverse phenomena with respect to strain energy density (work) and strain energy release (dissipation). @en

Understanding the relationship between the sensors’ outputs and the damage evolution within the joints is becoming increasingly crucial to improving structural health monitoring systems and collecting data to improve the joint’s design. Therefore, a study of the acoustic emission method associated with visual fracture evaluation was proposed to give insights into the toughening of composite bonded joints and better understand the relationship between the acoustic emission features and the damage mechanism involved. Thus, two different layups were proposed for the substrates: [0]8 and [0/902/0]S. In addition, a toughened epoxy adhesive with an embedded carrier (AF163-2k) was used to bond the substrates. Five specimens of each stacking sequence were tested under quasi-static mode I loading conditions. A travelling microscope and a regular digital camera were used on the lateral sides of the specimens to track the crack propagation paths. One piezoelectric sensor linked to the AMSY-6 Vallen system was used to assess the acoustic emission features produced within the joints during the tests. Unsupervised machine learning algorithms based on artificial neural networks and the Morlet continuous wavelet transformation were used to pattern recognition of the acoustic emission data. Self-organising maps, together with k-means algorithms, were used for data clustering. Following that, the acoustic emission features of each cluster were associated with the insights obtained from the crack propagation images. Finally, it was observed that the different layups triggered simultaneous toughening mechanisms. The combination of the acoustic emission and the visual evaluation was crucial for a deeper understanding of the underlying phenomena.@en

The relationship between the response of backface strain distributed sensing by Optical Backscatter Reflectometry and the damage in the adhesive was studied using double cantilever beam specimens. Digital Image Correlation and visual inspection provided information about the crack-tip position and the extension of the cohesive process zone. The comparison between the features of the backface strain pattern and the position and size of the cohesive zone led to the conclusion that, for the studied adhesive, backface distributed sensing allows for the onset of plastic deformations ahead of the crack-tip to be identified, opening new perspectives for fatigue crack monitoring and in-service measurements.@en

The feasibility of acoustic emission structural health monitoring to detect, localise and monitor crack propagation during quasi-static mode I loading of adhesively bonded joints was studied. Unsupervised artificial intelligence pattern recognition methods (Self-Organised maps and K-means) were used to classify acoustic emission raw data as either background noise or relevant information. After that, three different time-of-arrival picking algorithms were considered and implemented to determine the acoustic emission source's location, and their accuracy was discussed. Localised acoustic emission events were divided into well-defined groups with different energy levels and compared to Digital Image Correlation and visual evaluation results. It was possible to conclude that the highest energetic group allows the assessment of the onset of plasticisation ahead of the crack-tip within the studied adhesive, bringing novel standpoints to the use of acoustic emission as a structural health monitoring method for adhesively bonded joints.@en

The feasibility of applying Optical Backscatter Reflectometry as a backface strain monitoring method for bonded joints subjected to mode I fatigue crack propagation was studied. Visual evaluation and Digital Image Correlation methods were applied to track the crack-tip position and the onset of plasticisation in the adhesive, respectively. The methods were compared to understand the relationship between the changes in the optical fibre measurements and the crack propagation. The absolute maximum strain values gave important information about the crack propagation stage (stable or high velocity) within the adhesive and fast-rate crack propagation, which resulted in a sudden increase in strain values. Finally, the strain peak position was found to be a valuable indicator of crack tip position.@en

The use of adhesively bonded joints has increased considerably due to their lightweight, relevant strength-weight ratio and possibility to join multi-materials. Nevertheless, there are still some challenges in the application of this kind of joints in primary structures, such as guaranteeing their reliability during the components’ useful life. Structural health monitoring methods are suggested to ensure in-service safety and reliability of adhesive joints. The acoustic emission appears promising because it can detect the elastic waves produced within the material when it is under damage or straining. This research focuses on mode I fatigue damage monitoring metallic double cantilever beam adhesively bonded joints using the acoustic emission method. Digital image correlation and visual evaluation were applied during fatigue interruptions to track the crack-tip position within the adhesive and correlate them with the acoustic emission outcomes. The acoustic emission method is susceptible and different kinds of waves (background, friction and damage) can be easily assessed during the tests, producing an immense amount of data. So, unsupervised artificial neural networks for patterning recognition were proposed. Self-organising maps and k-means algorithms were used for data clustering and then classified regarding their sources. Finally, the acoustic emission results, digital image correlation and visual evaluations were compared.@en