DEM–compartment–population balance model for particle coating in a horizontal rotating drum. (24th March 2015) - Kumar, Rahul; Freireich, Ben; Wassgren, Carl
Abstract: A multi-scale modeling approach combining the discrete element method (DEM), a compartment model, and a population balance (PB) has been used to predict inter-particle coating variability in a horizontal, rotating drum. In previous studies using compartment models, compartments were devised using a least squares fit to the spray zone residence time per pass (the time particles spend in the spray during a single pass through the spray zone) and the cycle time (the time between successive visits to the spray zone) distributions. In this work, the difficulties associated with measuring these time distributions are highlighted. In particular, the use of time and area thresholds used to eliminate short duration residence time correlations results in significant differences in the time distributions. A new approach that does not require area or time thresholding is used here. A compartment model consisting of a spray zone and active and passive bed zones is proposed based on the motion of the particles in a rotating drum. The parameters for the resulting coupled set of PB equations are estimated by fitting the time varying coating mass variability curve from the first few tens of seconds (35–85 s) of DEM simulation data. The long term coating mass variability (1000 s) is predicted using the PB model and compared with direct measurements from the DEM simulations. Excellent agreement was obtained between the model and DEM simulations with a relative error of less than 5% for the three cases studied. A sensitivity analysis of the parameters on the model predictions shows that the size of the active bed zone and the time scale of the exchange between the active and passive bed zones have a strong influence on the coating variability. The effective time distributions for the PB-generated spray zone residence time per pass and the cycle time were also found to be significantly different than those obtained from DEM using time or area thresholding. This new modeling approach significantly reduces the computational time required to study the particle coating process as compared to only using DEM. Highlights: A novel GPU-based spray algorithm is proposed. Area/time threshold values have a significant influence on time distributions. Compartment-based PB model is developed for a rotating drum. The compartment–PB model accurately predicts CoV data. The DEM–compartment–PB modeling approach can be much faster than DEM alone.