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For a 3D orthogonal carbon fibre weave, geometrical parameters characterising the unit cell were quantified using micro-Computed Tomography and image analysis. Novel procedures for generation of unit cell models, reflecting systematic local variations in yarn paths and yarn cross-sections, and discretisation into voxels for numerical analysis were implemented in TexGen. Resin flow during reinforcement impregnation was simulated usingComputational Fluid Dynamics to predict the in-plane permeability. With increasing degree of local refinement of the geometrical models, agreement of the predicted permeabilities with experimental data improved significantly. A significant effect of the binder configuration at the fabric surfaces on the permeability was observed. In-plane tensile properties of composites predicted using mechanical finite element analysis showed good quantitative agreement with experimental results. Accurate modelling of the fabric surface layers predicted a reduction of the composite strength, particularly in the direction of yarns with crimp caused by compression at binder cross-over points.

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Resin transfer moulding is one of several processes available for manufacturing fibre-reinforced composites from dry fibre reinforcement. Recently, dry reinforcements made with Automated Dry Fibre Placement have been introduced into the aerospace industry. Typically, the permeability of the reinforcement is assumed to be constant throughout the dry preform geometry, whereas in reality, it possesses inevitable uncertainty due to variability in geometry. This uncertainty propagates to the uncertainty of the mould filling and the fill time, one of the important variables in resin injection. It makes characterisation of the permeability and its variability an important task for design of the resin transfer moulding process. In this study, variability of the geometry of a reinforcement manufactured using Automated Dry Fibre Placement is studied. Permeability of the manufactured preforms is measured experimentally and compared to stochastic simulations based on an analytical model and a stochastic geometry model. The simulations showed that difference between the actual geometry and the designed geometry can result in 50% reduction of the permeability. The stochastic geometry model predicts results within 20% of the experimental values.