Modeling deep-bed grain drying using Comsol Multiphysics

CFD simulations were carried out to predict the convective heat and mass transfer coefficients in the rice bed, and correlations were developed for the convective heat and mass transfer coefficients as a function of drying air flow rate. The developed correlations were used to extend the coupled CFD and diffusion model developed by ElGamal et al. (2013) for thinlayer rice drying to volumetric heat and mass transfer in a deep-bed of rice. All mathematical models were solved using the Comsol Multiphysics® simulation program v4.3 (Comsol Inc, Palo Alto), which uses the finite element method to solve the model equations. The model was used to predict the air temperature, as well as the grain moisture content and temperature at different locations of the dryer during the drying process. The theoretical predictions of moisture and temperature profiles inside a deep-bed of rice were verified by experimental data from literature

Multi-scale model for heat and mass transfer during rice drying

Grain drying is a simultaneous heat and moisture transfer problem. The modeling of such a problem is of significance in understanding and controlling the drying process. The main goal of this study was to predict the heat and mass transfer processes during deep-bed rice drying. To achieve this, first, CFD simulations were carried out to analyze the external flow and temperature fields at steady-state for a control volume of a stationary rice bed. The model was used to predict the convective heat and mass transfer coefficients in the rice bed, and correlations were developed for the convective heat and mass transfer coefficients as a function of drying air flow rate. Then, the coupled CFD and diffusion model developed by ElGamal, Ronsse, Radwan & Pieters (2013) to investigate the heat and mass transfer for thin-layer drying of rice was extended to volumetric heat and mass transfer in a deep-bed of rice using the predicted heat and mass transfer coefficients. All models were solved numerically using the finite element method. The model was used to predict the air temperature, as well as the grain moisture content and temperature at different locations of the dryer during the drying process. The theoretical predictions of moisture and temperature profiles inside a deep-bed of rice were verified by experimental data from literature. The average mean relative deviation values for the prediction of grain moisture content varied between 1.00 to 3.13%

A global coating quality model for top-spray fluidized beds: spray sub model

Fluidized beds are amongst others used in industrial applications for coating particles. Little research has been performed in developing a quality model for a coating process. A quality model is able to predict the quality of the process in terms of coating thickness and uniformity and the occurrence of unwanted side-effects, including agglomeration, attrition and spray loss. The quality of the coating process in a fluidized bed is largely determined by the spray characteristics and the particle motion. A new quality model was developed for the coating process in a top-spray fluidized bed. The first step in the development of the new model was the creation of an accurate spray sub-model that describes the movement and the heat and mass balances of the droplets in the coating process. The second step was the creation of a particle sub-model that describes the movement and the heat and mass balances of the particles in the fluidized bed. The third and final step will be the development of the global coating quality model by combining the spray and the particle sub model. Experimental validation of the spray sub-model has already been carried out and is presented in this paper