(667b) Scaling of Heat Transfer and Temperature Distribution in Granular Flows in Rotating Drums | AIChE

(667b) Scaling of Heat Transfer and Temperature Distribution in Granular Flows in Rotating Drums


Yohannes, B. - Presenter, Rutgers University
Emady, H., Arizona State University
Paredes, I. J., Rutgers, the State University of New Jersey
Javed, M., Rutgers University
Borghard, W., Rutgers University
Muzzio, F. J., Rutgers, The State University of New Jersey
Glasser, B., Rutgers University
Cuitiño, A., Rutgers, the State University of New Jersey
Rotating drums are one of the most common devices used for industrial processes that involve thermal treatment of granular materials. To improve efficiency, several factors, including the physical, mechanical, and thermal properties of the powder & calciner, as well as, operating conditions such as feed rate and speed of rotation, need to be considered. A powerful approach towards achieving an efficient process is to develop predictive models for the particlesâ?? temperature distribution (space & time), particularly for the purposes of scale-up from laboratory scale experiments. We used discrete element method (DEM) simulations to study the scaling of particlesâ?? temperature distribution in rotating drums at low temperatures, where conduction through particle-particle and particle-wall contact area is the dominant heat transfer mechanism. A wide range of several particle properties and operating conditions were considered in the simulations. Based on the results, we show that the most important timescales relevant to the heat transfer process are the time to heat up a single particle to the drum wall temperature and the time of contact between a particle and the drum wall. Then, using these timescales, we developed a model to predict the particlesâ?? temperature distribution at any time during the heating process. All of the simulations can be collapsed into one relationship. This model can be used to predict the required time to heat up all particles to the desired temperature. The results from this model also compare very well with experimental results conducted at low temperatures.