Abstract:For brittle fracture behaviour of carbon fibre reinforced plastics (CFRP) under compression, several approaches exist, which describe different mechanisms during failure, especially at stress intensifications. The failure process is not only initiated by the buckling fibres, but a shear driven fibre compressive failure beneficiaries or initiates the formation of fibres into a kink-band. Starting from this kink-band further damage can be detected, which leads to the final failure. The subject of this work is an experimental investigation on the influence of ply thickness and stacking sequence in quasi-isotropic CFRP laminates containing stress intensifications under compression loading. Different effects that influence the compression failure and the role the stacking sequence has on damage development and the resulting compressive strength are identified and discussed. The influence of stress intensifications is investigated in detail at a hole in open hole compression (OHC) tests. A proposed interrupted test approach allows identifying the mechanisms of damage initiation and propagation from the free edge of the hole by causing a distinct damage state and examine it at a precise instant of time during fracture process. Compression after impact (CAI) tests are executed in order to compare the OHC results to a different type of stress intensifications. Unnotched compression tests are carried out for comparison as a reference. With this approach, a more detailed description of the failure mechanisms during the sudden compression failure of CFRP is achieved. By microscopic examination of single plies from various specimens, the different effects that influence the compression failure are identified. First damage of fibres occurs always in 0°-ply. Fibre shear failure leads to local microbuckling and the formation and growth of a kink-band as final failure mechanisms. The formation of a kink-band and finally steady state kinking is shifted to higher compressive strains with decreasing ply thickness. Final failure mode in laminates with stress intensification depends on ply thickness. In thick or inner plies, damage initiates as shear failure and fibre buckling into the drilled hole. The kink-band orientation angle is changing with increasing strain. In outer or thin plies shear failure of single fibres is observed as first damage and the kink-band orientation angle is constant until final failure. Decreasing ply thickness increases the unnotched compressive strength. When stress intensifications are present, the position of the 0°-layer is critical for stability under compression and is thus more important than the ply thickness. Central 0°-layers show best results for OHC and CAI strength due to higher bending stiffness and better supporting effect of the adjacent layers.

Common analytical models to predict the unidirectional compressive strength of fibre reinforced polymers are analysed in terms of their accuracy. Several tests were performed to determine parameters for the models and the compressive strength of carbon fibre reinforced polymer (CFRP) and glass fibre reinforced polymer (GFRP). The analytical models are validated for composites with glass and carbon fibres by using the same epoxy matrix system in order to examine whether different fibre types are taken into account. The variation in fibre diameter is smaller for CFRP. The experimental results show that CFRP has about 50% higher compressive strength than GFRP. The models exhibit significantly different results. In general, the analytical models are more precise for CFRP. Only one fibre kinking model’s prediction is in good agreement with the experimental results. This is in contrast to previous findings, where a combined modes model achieves the best prediction accuracy. However, in the original form, the combined modes model is not able to predict the compressive strength for GFRP and was adapted to address this issue. The fibre volume fraction is found to determine the dominating failure mechanisms under compression and thus has a high influence on the prediction accuracy of the various models.