On-Line Characterization of Bulk Permeability and Race-Tracking During the Filling Stage in Resin Transfer Molding Process

Abstract

Resin Transfer Molding (RTM) is widely used to manufacture polymer composite materials. In this process, the fiber preform is placed in a closed mold and thermoset resin is injected to saturate the preform. After the resin cures the mold is opened and the net shape composite part is obtained. With RTM, one is capable of making complex and high quality composite parts with short cycle times. However, by introducing more complexity into the part, one also introduces higher probability of disturbances, such as race-tracking of resin during impregnation along preform edges. This can lead to incomplete saturation of fiber preform forming flaws such as dry spots in the composite part. The strength and existence of race-tracking is a function of the fabric type, perform manufacturing method, and their placement in the mold. It can vary from one part to the next in the same production run and usually it is not repeatable. The characterization of race-tracking and preform permeability is a key input for simulation tools that optimize the gates and vents locations and for designing advanced sensing and flow control strategies. This paper describes a method to estimate the strength and location of race-tracking and characterize the preform bulk permeability during the resin impregnation stage of RTM. The approach can be described in two steps. The first step generates simulations off line that map the overall range of potential disturbances likely to occur during the injection. The second step uses sensors placed in the mold, which allow one to identify the simulation within the database that resembles the experiment in terms of the filling behavior during the filling stage on the manufacturing platform. In the final step, this information is used to estimate race-tracking strength and location as well as the bulk permeability. Both experimental and numerical case studies show the reliability and accuracy of this method. It could be utilized for a broad range of applications such as active flow control, vent location optimization, and process monitoring of mold filling processes.