| Summary: | Fibre Reinforced Plastics offer several advantages over other materials such as decreased part counts, weight savings, and flexibility. The obstacles to the further expansion of composites use, particularly in cost-conscious industries such as the car industry, include volume, cost, and quality. Liquid Composite Moulding, where the dry textile reinforcement is shaped prior to application of the plastic matrix, offers to address these drivers by offering potential for automation, speed, and quality control. However, the preforming of the dry reinforcement is rarely automated, and its results are variable and hard to predict or control. This thesis aims to facilitate better preforming process design and control. The dominant deformation mechanism that allows reinforcements to conform to a 3D surface is trellis shear. Work is therefore presented on shear characterisation of textile reinforcements using the picture frame and the bias extension tests. Several approaches to normalising these tests to achieve method-independent shear data are proposed, and compared. Of these, a normalisation technique for the bias extension test based on energy considerations appears to be the most appropriate. A constitutive modelling approach, based on the meso-mechanical deformation mechanisms identified in the reinforcement, is developed for characterising the asymmetric shear properties exhibited by non-crimp fabrics. The results from this model are compared with experimental data. Finally, an energy minimising kinematic drape method is developed to account for the use of automated reinforcement blank-holders, and methods for modelling process variability using the code are investigated.
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