Homogenous Modeling of VARTM Processes with Hybrid Layered Media

Abstract

Numerical methods have been widely used to simulate vacuum assisted resin transfer molding (VARTM) processes to obtain optimum process parameters. Many VARTM parts have very large in-plane dimensions compared to the thickness. However, the incorporation of a highly permeable distribution media on the surface of a fibrous preform results in significant through thickness flow particularly at the flow front where large gradients can exist. In general, flow simulations that can model the distribution media as a discrete layer are needed, which, however, significantly increases the number of elements and thus computational costs in the numerical analyses. The present study introduces a homogenous preform system using equivalent porosity and permeability over the out-of-plane direction that retains the through-thickness flow characteristics in order to reduce complexity in modeling the distribution media in VARTM processes. First, a mass-average approach was developed to reduce the number of dimensions that needs to be modeled (e.g., 3-D is reduced to 2-D in-plane and 2-D cross section is reduced to a 1-D flow problem). Parametric studies were carried out over a reasonable range of the input parameters such as preform thickness, length, porosity, and permeability and showed limitations in using the mass average approach with homogenous models. Second, a reconstruction method was developed to predict accurately the flow pattern in the out-of-plane direction from the homogenous models. The flow pattern was successfully reconstructed using the flow data obtained from the homogenous model with an analytic solution of the flow front shape in the out-of-plane direction. Average flow front locations and the flow front patterns were investigated by numerical analyses for a few flow scenarios, which validated the present methods and quantified error levels in the resin flow pattern and resin fill time. The mass-average and reconstruction approaches successfully estimated the resin flow locations and patterns with respect to time and significantly reduced complexity in modeling complex geometries as well as computational costs.