| Summary: | This work describes an experimental investigation of the effect of through-thickness stitching on the in-plane crack growth of Resin Film Infused (RFI) carbon fibre/epoxy laminates. Through-thickness reinforcement is a relatively recent approach to compensate for poor out-of-plane mechanical properties in laminated materials and also as a new method of joining laminated aerospace structures. The effect of Kevlar® stitching on the fracture response of RFI laminates was successfully evaluated using an overheight compact tension (OCT) specimen. It had previously been proven that this small notched geometry allows for stable self-similar damage growth (including fibre failure) in composite laminates, under controlled loading conditions. This work further analyses the usefulness of the OCT geometry. A detailed physical description of damage initiation and propagation in the process zone, (the area of discontinuous damage ahead of the notch tip) was obtained from measurements of surface displacement fields, as well as sectioning and deplying of the failed laminate. The experimental results yield valuable information that may be used to calibrate a finite element model. The fracture response of these materials was largely unaffected by stitching, except results indicate that poor control of stitch tightness during manufacturing affects the type of damage evolved. When notched perpendicular to, but loaded parallel to the stitching, 'tight' stitching does not inhibit the natural tendency of these RFI materials to delaminate, resulting in crack blunting. However, 'loose' stitching results in a more brittle response — damage grows in a self-similar manner across the specimen width, and consists of heavy fibre breakage in plies oriented to the direction of load. Tested specimens with loose stitching also exhibit significantly less delamination. Finally, the development and size of the fracture process zone was examined by comparing the experimental data and specimen compliances generated from a simple finite element model.
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