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DEVELOPMENT OF A MULTI-SCALE MODEL FOR DEEP-BED DRYING OF RICE.

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Title: DEVELOPMENT OF A MULTI-SCALE MODEL FOR DEEP-BED DRYING OF RICE.
Authors: ElGamal, R.1, Ronsse, F.2, ElMasry, G.3, Pieters, J. G.4 Jan.Pieters@UGent.be
Source: Transactions of the ASABE. 2015, Vol. 58 Issue 3, p849-859. 11p.
Abstract: The drying behavior of rough rice in a deep bed was analyzed numerically by solving the heat and moisture transfer equations using a novel deep-bed model. The model consisted of two scales. A computational fluid dynamics (CFD) model was used first to predict the convective coefficients of heat and mass transfer between an individual rough rice kernel and air in the rough rice bed. The predicted heat and mass transfer coefficients were then used for coupling the moisture and heat fluxes inside the rough rice kernel with the external convective heat and mass transfers at the kernels' surfaces in a complete rough rice bed model using the Comsol Multiphysics simulation environment. The developed model was used to predict the grain moisture contents and temperatures at different heights in the bed during drying. The theoretical predictions of moisture profiles inside a deep bed of rough rice were validated against experimental data from literature. The results revealed that the mean relative deviation between predicted and experimental values varied between 3.1% and 6.8%. Most importantly, the novel approach used in this study allowed the deep-bed model to predict the moisture and temperature distributions inside the individual rough rice kernels at different heights in the rough rice bed. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:The drying behavior of rough rice in a deep bed was analyzed numerically by solving the heat and moisture transfer equations using a novel deep-bed model. The model consisted of two scales. A computational fluid dynamics (CFD) model was used first to predict the convective coefficients of heat and mass transfer between an individual rough rice kernel and air in the rough rice bed. The predicted heat and mass transfer coefficients were then used for coupling the moisture and heat fluxes inside the rough rice kernel with the external convective heat and mass transfers at the kernels' surfaces in a complete rough rice bed model using the Comsol Multiphysics simulation environment. The developed model was used to predict the grain moisture contents and temperatures at different heights in the bed during drying. The theoretical predictions of moisture profiles inside a deep bed of rough rice were validated against experimental data from literature. The results revealed that the mean relative deviation between predicted and experimental values varied between 3.1% and 6.8%. Most importantly, the novel approach used in this study allowed the deep-bed model to predict the moisture and temperature distributions inside the individual rough rice kernels at different heights in the rough rice bed. [ABSTRACT FROM AUTHOR]
ISSN:21510032
DOI:10.13031/trans.58.10904