Catalyst impregnation is one of the most important steps in preparing industrial catalysts. In this procedure, metal salts or complexes are dissolved in a usually aqueous solution and then contacted on a porous oxide catalyst support. Here, alumina (Al2O3) is used as the porous oxide catalyst support and pure water is sprayed in a double-cone blender. Simulations were performed using DEM (Discrete Element Method) calculations between particles to determine their behavior during the absorption process. Because of the myriad number of calculations that must be done for a single simulation, we simulate one third of the actual impregnation process. A novel water transfer algorithm was implemented in the simulations to reproduce the actual distribution of water in the particle bed. We computed a number of parameters such as the residence time distribution (time that the particles spend under the spraying zone), the extent of the dead zones (zones that do not receive any water during the impregnation process) and the spatial distribution of the sprayed water throughout the powder bed in different cut planes. After examining the system under a variety of conditions, the residence time distribution seemed to be profoundly affected by any difference in spraying gun setup. However, after a given number of revolutions, the residence time distribution looked similar for increasing amount of revolutions. After characterizing the dynamics of the impregnation process, experiments were performed to substantiate our computer-generated data. Ultimately, a large number of variables affect the sorption rate of water onto these particles including: size and number of spray nozzles, distance from the center of the drum, number of rotations of the drum, and duration of the spraying. For all impregnator configurations there is a presence of dead zones and therefore the liquid is never distributed completely homogeneously throughout the powder bed. However, if we correctly manipulate the variables and the configuration of the spraying guns we can obtain a nearly homogeneous distribution.