(135d) CFD-DEM Simulation for Drying of Food Grain in a Fluidised Bed
World Congress on Particle Technology
2018
8th World Congress on Particle Technology
Fluidization & Multiphase Flow
Computational Approaches to Multiphase Heat, Mass Transfer & Reactive Chemistry II
Monday, April 23, 2018 - 4:36pm to 4:58pm
Drying is a common practice for food grain processing, mainly to prevent postharvest deterioration, to restrict microbial growth and to extend storage time. Drying of food grains by gas consumes huge thermal energy and it is of importance to improve its energy efficiency by optimization and integration of drying processes. Numerical approach is a cost-effective alternative way of experimental approach for optimisation and modification of the existing drying processes. A combined computational fluid dynamics (CFD) - discrete element method (DEM) numerical model has been developed to provide an accurate and detailed predictions for both fluid and solid phases of fluidised bed drying. The model is incorporated with a simple drying model to consider water evaporation as a resemblance to chemical reaction. The developed model can provide both macroscopic and microscopic drying characteristics such as drying kinetics and moisture content of individual particle. First, the model is validated by comparing the predicted drying rate curve and temperature profile with the experimental data, showing good agreement. Then, a parametric study has been conducted based on the validated model to examine the effects of different operational conditions and grain properties on drying rate, thermal efficiency and moisture distribution of particles. The model follows a general understanding of drying that drying rate increases with the increase of air velocity and air temperature, and the decrease of initial moisture content and particle size. Thermal efficiency of dryer increases with increasing temperature and decreasing air velocity, initial moisture content and particle size. However, the standard deviation of moisture distribution of particles (obtained at a given mean moisture content) decreases with the increase of air velocity or particle size and the decrease of temperature or initial moisture content. Based on particle scale information, new finding is revealed that is, higher air velocity, higher particle size, lower temperature or lower initial moisture content gives more uniform moisture distribution of particles. Such a particle scale model would be useful for designing and controlling drying processes.