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Modeling to Predict Micro-scale Permeability for Fiber Reinforcement in Liquid Composite Molding



In liquid composite manufacturing, permeability is the driving process parameter for mold fills and is critical for understanding the infusion flow and pressure distribution that results. Permeability has been identified as a complex variable which can vary significantly in magnitude for similar test cases. Permeability has also been isolated at different levels because of the multi-scale nature of composite fiber reinforcement. In the micro-scale, fibers are formed into randomly aligned tows composed of thousands of fibers. A second scale, the meso-scale, considers the tow dimensions and weave parameters, but inputs a Darcy based permeability to make up for physical geometry variations. On the micro-scale, fibers are generally considered as ordered in some kind of idealized packing arrangement, for example hexagonal or square packing. This is not always realistic and defining permeability as a function of porosity alone may not be enough to achieve an accurate permeability prediction on the micro-scale. Here, we isolate the micro-scale structures of unidirectional fiber reinforcements and investigate flows across aligned fiber geometries and infusion characteristics during manufacturing. Reduced geometries are utilized to represent the fiber and matrix interactions during a liquid infusion. The overarching goal of this research is to use numerical tools to create better understanding of composite manufacturing processes. A systematic computational approach is utilized to understand how material packing changes the fluid flow regime during composite manufacturing, helping to select appropriate infusion parameters to produce a part. This approach incorporates a numerical modelling procedure to predict unidirectional permeability on the microscale. The results set up a baseline that compares well with analytical models as a function of fiber diameter and volume fraction. Results show that variations due to fiber packing can be identified independently of fiber volume fraction.

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