Resin transfer molding (RTM) is one of the most widely used composite manufacturing processes for lightweight fiber-reinforced plastic components which has many applications in automotive and aerospace industries. This process is known to yield outstanding strength-to-weight characteristics, a high glass-to-resin ratio, and increased laminate compression. In this method, reinforcement is placed in the mold, which is then closed and clamped. A low viscosity resin is then pumped in under pressure, displacing the air and venting it at the edges, until the mold is filled. Molds for this low-pressure system are usually made from composite or nickel shell-faced composite construction.
There exist two matters of great concern in modeling RTM, i.e., (i) the accurate prediction of resin and porous matrix temperature histories to prevent the resin from turning into a gel before the cavity is filled and degrading the composite, and (ii) the prediction and measurement of permeability of reinforcement in order to predict the formation of flow front precisely. The formation of the flow front in the resin injection process affects the quality of the finished composite in terms of the void formation.
In this work, I developed a method to obtain the permeability, components of anisotropic thermal conductivity (transverse and longitudinal), stagnant thermal conductivity, and dispersion thermal conductivity of fibrous porous matrix in the mold. The injection part of the RTM process is modeled as a transport of resin flow through a porous medium in a long rectangular channel. By comparing the numerical results to the available experimental data, the effective thermal conductivity of a fibrous porous medium is obtained. Also, various models for the prediction of stagnant thermal conductivity are compared and a correlation is then recommended for the prediction of dispersion thermal conductivity. Finally, the effects of structural parameters, such as porosity and permeability on the centerline temperature distribution and the outlet velocity profile in the channel, are investigated.