Title : Creation of Material Twin Geometric Models of Continuous Fiber Composites Based on X Ray Microtomography
Engineering textiles are used as fibrous reinforcements in high performance polymer composites. The mechanical and flow properties of continuous fiber composites depend on their dual-scale porous structure. Depending on the flow front velocity during fabrication by Liquid Porous Molding (LPM), long and elongated microscopic open spaces (micropores) may appear between the filaments of fiber tows, or up to two orders of magnitude larger mesoscopic spaces (mesopores) can be created between yarns. Because of this complex material structure and due to intrinsic material variability of high performance composites, numerical predictions are not easy. To achieve this goal, X-ray microtomography (Micro-CT) can be used to provide detailed information on the geometric mesostructure of continuous fiber composites. A new approach will be presented to construct detailed geometric models of engineering textiles from Micro-CT three-dimensional (3D) images. These models are called “material twins”, if they possess three distinctive features: (1) they are representative of material variability; (2) their accuracy can be evaluated; and (3) computer simulations can be carried out to predict mechanical and flow behavior. This new and general methodology will be applied to create the material twin model of a 2D plain woven fabric. By introducing a new multiple factor morphological accuracy criterion, the quality of the “material twin” reconstruction can be compared to models obtained by standard image processing techniques or based on textile modeling software. Material twin models allow performing computer analysis to predict material properties. Hence, the creation of a virtual laboratory based on this approach can be contemplated. Examples of results for permeability prediction will be given. Finally, it will also be shown how accounting for material variability in this virtual analysis turns out to be a critical issue for high performance composites to ensure a successful comparison of numerical predictions with experimental results.