Investigation of the electrical resistance change of carbon fibre composites in the presence of damage

Carbon fibre reinforced polymers (CFRP) are widely used in the aerospace, automotive, and renewable energy sectors due to their high strength-to-weight ratio and tailorability. However, their inherent susceptibility to internal damage, such as fibre fracture, matrix cracking, and delamination, often undetectable from the surface, poses a major challenge for safety-critical applications. The ability to detect such damage in real-time, without disassembling the structure, has made Structural Health Monitoring (SHM) an increasingly attractive solution. Among several SHM techniques, electrical resistance-based methods offer a low-cost, approach with the potential for integration directly into the composite structure. This thesis investigates the application of electrical resistance change for damage detection in CFRP laminates, with a focus on unidirectional (UD) and hybrid configurations. A new analytical model is developed to predict electrical resistance in UD CFRPs with 0° or 90° fibre orientations instrumented with small surface electrodes. The model introduces two parameters, effective width and effective electrode distance, which account for geometry and fibre direction, enabling resistance prediction between any two surface electrodes. Validation through finite element modelling and experimentation demonstrates strong agreement and highlights the model's potential as a design tool for electrode arrays for damage sensing. Building on this foundation, the thesis introduces and validates the unit cell sensing concept to detect damage in composite materials, implemented in two configurations: cross-ply sensing laminates and serpentine sensing strips. These configurations are analysed both numerically and experimentally. The serpentine design, in particular, demonstrates superior sensitivity to micro-cracks, detecting crack lengths as small as 1.5 mm (1% of the studied unit cell width) using only two electrodes. This result underscores the potential for scalable and cost-effective SHM systems adaptable to large-area composite structures. Carbon fibre fracture initiation and propagation are also studied in hybrid glass/carbon laminates subjected to cyclic and monotonic tensile loads. The electrical resistance response is strongly influenced by carbon layer thickness and fibre type. Thin laminates (one or two carbon layers) with laminate thickness between 0.03 mm and 0.1 mm show progressive and continuous resistance increases due to fragmentation and local delamination, while thick laminates (three or four layers), with laminate thickness between 0.09 mm and 0.2 mm display a switch behaviour acting like an open-circuit following fibre rupture and extensive delamination. To evaluate real-world applicability, serpentine sensors are embedded within composite substrates and subjected to quasi-static indentation. These tests reveal clear correlations between force and resistance change, dependent on sensor placement (top, middle, bottom). Notably, M46JB and YSH70carbon fibre sensors produced measurable resistance shifts aligned with damage progression, while T300 carbon fibre sensors showed minimal response due to its higher failure strain. Cyclic loading on both pristine and pre-triggered sensors demonstrates the sensor's ability to monitor crack initiation, reopening, and closure, even in the absence of macroscopic mechanical degradation of the substrate. These results underscore the sensor’s capacity for early-stage detection and post-damage diagnosis. In conclusion, this thesis provides a validated methodology for designing electrical resistance-based SHM systems for CFRPs. It demonstrates that effective damage detection depends on an approach combining sensor architecture, fibre type, and strategic sensor placement based on expected stress distributions and failure modes. These insights advance the development of next-generation smart composites, with embedded sensing capabilities tailored for aerospace, wind energy, and other high-performance applications.