(194a) Impregnation of Catalyst Particles in a Rotating Drum with Baffles: Systematic Study Using Discrete Element Methods and Mass Transfer Theory

In this study we present Discrete Element Method (DEM) simulations in a rotating drum with baffles, coupled with a previously developed algorithm for fluid transfer to model dry catalyst impregnation with the goal of improving the liquid content uniformity of the resulting catalyst particles. We did a systematic study of the effect baffles to the distribution of liquid in the particle bed. We vary the number of baffles from 2 to 16, the fill level, the size and orientation of the baffles, the speed of rotation and the angle of inclination of the baffles. We also propose a mass transfer theory model to predict results theoretically. Our studies show that smaller angles give a smaller relative standard deviation (RSD) than larger angles. Smaller angles work better than straight baffles. The best case was parallel orientation with 20 degrees of inclination. Best RSD’s are for the largest baffle height for all cases considered. Parallel orientation works better than opposite orientation. We also observe 2 baffles with parallel configuration with small angles have similar performance that 4 baffles straight. We also see that tilting of the baffles is equivalent to adding more baffles. If baffles are straight a larger number of baffles works better than a smaller number. Our results show that straight baffles do not generate significant convection in the axial direction. Particles behave as a rigid body in the passive zone. Wider baffles provide larger convection in the axial direction, thus smaller RSD. For straight baffles there is an optimal number of baffles. The larger the baffle height d, the smaller the Relative Standard Deviation. Baffles provide a means of accelerating the particles in the cascading zone.

The culmination of this work has been the development of simulations capable of analyzing dry catalyst impregnation in limitless parameters, geometries, and conditions for improving overall mixing, content uniformity, and product quality.