Catalytic converters are critical devices in automotive vehicles; they convert the toxic exhaust from internal combustion engines into less harmful byproducts. In a catalytic converter, catalytic particles line a porous substrate and react with the automotive exhaust as it flows through the structure. Aerogels are highly porous materials which could be used in catalytic converters. Theoretically, this high porosity should allow for more surface area on which catalytic reactions can occur and thus increase the effectiveness of the catalytic converter. Experimental research has shown the promise of using aerogels in catalytic converters, and there is a need for computational modeling to optimize the aerogel structure. In this research, a computational model was developed for flow through aerogel materials to study the impact of aerogel properties, such as porosity, on the catalytic potential. The Lattice Boltzmann (LB) method was implemented for the fluid flow model and the Diffusion Limited Cluster Aggregation (DLCA) method was used to create computational models of aerogel structures. Current results demonstrate the feasibility of using the LB method in conjunction with the DLCA method to model this fluid flow. Future research will continue the development of this model so that it can be used to calculate the catalytic potential and optimize the aerogel structure.