(569c) Scaling Particle Dynamics in Rotating Drum Coaters

Authors: 
Kumar, R. - Presenter, IIT Bombay
Wassgren, C. R., Purdue University
Ban, J., Purdue



Scaling Particle Dynamics in Rotating Drum
Coaters

J. Ban, R. Kumar, and C. Wassgren

School of Mechanical Engineering

Purdue University

Abstract

Scaling  particle coating operations is an important
issue for a number of industries, including those that process pharmaceuticals,
consumer products, and chemicals.  Scaling of particulate processes, and
coating in particular, has been the subject of numerous experimental,
computational, and analytical studies. Unfortunately, a dependable scaling
method that fully translates data gathered at the lab scale to the industrial
scale does not exist, especially since geometric similarity is often neglected.
 This study investigates how imperfect particle size scaling affects the
particle dynamics and inter-particle coating variability in geometrically
similar pan coaters.  DEM computer simulations were used to model particle
movement in five different-sized rotating cylindrical drums, resulting in five
different drum to particle diameter ratios, with identical fill fractions and Froude
numbers.  Measurements of particle surface velocities and time spent in
the coating zone were made.  The spray
coating zone residence time coefficients of variance (CoVs)
were used to determine the degree of inter-particle coating variability.
 Surface velocity profiles show good agreement with those found in the
literature; however, the velocity scaling behavior is different.  The size
of the coating zone was found to have no influence on the long term CoV
behavior, a result that has not been described previously in the literature.
 Decreasing the drum to particle diameter ratio results
in reduced particle mixing and smaller CoV values after the same number of drum
rotations.  This last finding demonstrates that the current
approach to scaling without maintaining geometric similarity between the
particles and the drum can result in significant errors.  

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