FABRIC AND TEXTILE 3D PERMEABILITY CHARACTERIZATION WORK-STATION.

The manufacturing cost of using Liquid Composite Molding (LCM) processes has been mitigated with the use of flow simulations. Flow simulations can predict how the resin flows in a mold containing fiber preforms and can identify possible void formation locations. Simulations have been used over the last decade for mold and process design, process optimization and even process control. The results are very dependent on the input material parameters provided to the simulation. Most important of these parameters is the fiber preform permeability. Fiber preform permeability is a second order symmetric tensor which requires the determination of six independent components in any given coordinate system. For thin parts, 2D simulation is sufficient which requires only the in-plane permeability, either two principal values and the orientation of principal axes or two normal and one "skew" component. Several methods to obtain these values have been reported. For thick parts, particularly when distribution media is used on the part surface, through the thickness permeability is needed as well and can be measured and has been reported. However, three-dimensional tensor contains not only this (normal) transverse permeability but also two additional skew components. These are, in practice, neglected as it is assumed that fabric layering produces symmetry in the through thickness direction. This assumption is somewhat questionable in the first place, but it becomes truly invalid when thick, three-dimensionally woven or braided reinforcements are used. The geometry of weave with skew terms in the through thickness direction can influence the flow behavior and hence the void formation. In this study, we present a measurement work station that will provide all the six components of the permeability tensor from one experiment. The methodology uses flow visualization data to collect the flow front motion information and then couples it with a multi-objective optimization algorithm and our flow simulation tool, LIMS, to determine the permeability tensor. The entire process is automated and experimental results are superimposed on the simulation results. Permeability values in the simulation are updated until the error between the experimental and the simulation results is minimized for all permeability components. This algorithm is utilized with 3D preforms to test its applicability. The experimental results are discussed in terms of the applicability of the developed algorithm. [ABSTRACT FROM AUTHOR]