Addressing variability of fiber preform permeability in process design for liquid composite molding

Date
2015
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University of Delaware
Abstract
In Liquid Composite Molding (LCM) processes, reinforcing glass, carbon or Kevlar fiber preforms are placed in a mold cavity and a liquid resin is introduced to cover the remaining empty space to form a composite by curing the resin. The fiber preform permeability plays a key role in the filling pattern of the mold, which dictates if there will be any voids (empty spaces) in the composite. Permeability tensor describes the resistance to fluid flow through the anisotropic fibrous porous media, which may not be spatially uniform. The variability in the permeability due to the variation in the preform or its placement in the mold can influence the filling pattern and hence the quality of the part being manufactured. The permeability map of a preform specifies the values of components of the permeability tensor at various locations of the preform. The overall objective of this dissertation is to investigate various approaches and tools to create a permeability map that will ensure filling to achieve manufacturing success despite the variability of the filling pattern, a requirement of robust process design. When unidirectional fabrics are used to manufacture composites, they are typically stacked on top of each other to build up the desired thickness. A slight misalignment during the stacking can change the through-thickness permeability dramatically and the flow pattern due to the creation of low-resistance pathways. Experimental characterization of the out-of-plane or through-thickness permeability of a series of unidirectional fabrics stacked in various orientations is investigated. Also, numerical simulations are conducted to predict the effect of change in fiber orientation on the through-thickness permeability for unidirectional fabrics. Results demonstrate that the stacking sequence of the unidirectional fabrics influence the through thickness flow and hence the transverse permeability. Next, variation in the permeability value of the fibrous domain caused by the non-uniformity in fiber architecture is investigated. The time evolution and geometry of the rough interfaces of the fluid flow in porous medium are analyzed using the concepts of dynamic scaling and self-affine fractal geometry and is shown to belong to the Kardar-Parisi-Zhang (KPZ) universality class. Additionally, this characterization can be used to quantify the percentage of abnormalities within the preform from flow front profile analysis using KPZ formulation. Finally, a methodology is introduced to create a permeability map for a given mold geometry along with inlet and vent locations which will allow the mold to completely fill despite the variations in the preform and the flow disturbances caused due to its placement. The resin flow pattern can be manipulated with a tailored highly permeable layer (Distribution Media (DM)) layout to be placed on top of the preform as it does impact the flow patterns significantly. Thus, a predictive tool to design an optimal shape of DM, which accounts for the flow variability introduced due to race tracking along the edges of the inserts is presented by adapting a discrete optimization algorithm.
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