• Energy Research
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Abstract Drying is the most important post-harvest processing method for the long-term storage of food grains. Drying and related particle shrinkage are usually determined by various operational conditions and grain properties like grain size, density and initial moisture content. The impact of these food grain properties on drying and shrinkage is investigated by the recently developed computational fluid dynamics-discrete element method drying and shrinkage model. First, particle mixing in a fluidised bed and general drying characteristics are discussed followed by the contribution of different heat transfer modes on fluidised bed drying. The particle scale investigation found that the convective heat transfer is dominant, but the conductive heat transfer becomes important at low air velocities. Then the effect of grain size, density and initial moisture content on drying rate are quantified in terms of drying rate. The drying rate increases exponentially with decreasing grain size, but a slightly smaller drying rate is observed with decreasing initial moisture content and grain density. The shrinkage rate, resembling the drying rate, increases with decreasing grain size or increasing initial moisture content and grain density. Finally, the effects of these food grain properties on the drying quality, quantified by moisture and grain size distributions, are evaluated in this study. The grain scale results revealed that the uniformity of moisture and grain size distributions increases with increasing grain size, decreasing initial moisture content or decreasing grain density. The findings should be useful for a better understanding and control of the drying process in the fluidised bed.

Abstract Drying is a common practice for post-harvest processing of food grains. Fluidised beds are often adopted for this purpose. It is of importance to understand the fluidised bed drying process for improving its energy efficiency. This work establishes a numerical drying model based on the combined approach of computational fluid dynamics and discrete element method for describing heat and mass transfer in the gas-solid flow system. Water evaporation is modelled in resemblance to a chemical reaction, thereby requiring fewer model parameters. The model is first described in detail. Then it is tested by comparing model predictions with those experimental data of corn kernel from the literature. General drying characteristics including grain and air moisture contents are reproduced qualitatively. The predicted drying rate curves are quantitatively comparable with those of experimental data. Finally, the effects of inlet air velocity and temperature are examined. The model predictions confirm that the drying rate increases with both the inlet air velocity and temperature. However, the drying product quality, here represented by the standard deviation of grain moisture distribution, increases with increasing air velocity or decreasing air temperature. This grain scale model would be useful to the design and control of the drying process.

Abstract Food grains naturally undergo physical and structural changes during a drying process. The volumetric change of particles or particle shrinkage is one of the important and complicated physical changes in drying. In this work, a shrinkage model for particle diameter reduction is incorporated into the computational fluid dynamics- discrete element method (CFD-DEM) drying model for food grains. First, mixing, general drying and shrinkage characteristics including particle and air moisture content, and particle diameter variation are reproduced. Then, the model is tested by comparing the predicted moisture reduction and volume shrinkage curve with the experimental data of wheat from the literature. The results demonstrate the capability of the current model in predicting drying and particle shrinkage characteristics. Finally, the effects of inlet air temperature and velocity on drying and particle shrinkage are studied. It is revealed that the shrinkage rate increases significantly with increasing air temperature but increases slightly with increasing inlet air velocity. The uniformity of grain size, quantified here by the standard deviation of the particle diameter distribution, increases with decreasing air temperature or increasing air velocity. This grain scale drying model with particle shrinkage should be useful for the design and control of many drying processes.