Modeling pore structures and airflow in grain beds using discrete element method and pore-scale models
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Biosystems Engineering
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The main objective of this research was to model the airflow paths through grain bulks and predict the resistance to airflow. The discrete element method (DEM) was used to simulate the pore structures of grain bulks. A commercial software package PFC3D (Particle Flow Code in Three Dimension) was used to develop the DEM model. In the model, soybeans kernels were considered as spherical particles. Based on simulated positions (coordinates) and radii of individual particles, the characteristics of airflow paths (path width, tortuosity, turning angles, etc.) in the vertical and horizontal directions of the grain bed were calculated and compared. The discrete element method was also used to simulate particle packing in porous beds subjected to vertical vibration. Based on the simulated spatial arrangement of particles, the effect of vibration on critical pore structure parameters (porosity, tortuosity, pore throat width) was quantified. A pore-scale flow branching model was developed to predict the resistance to airflow through the grain bulks. Delaunay tessellation was also used to develop a pore network model to predict airflow resistance. Experiments were conducted to measure the resistance to airflow to validate the models. It was found that the discrete element models developed using PFC3D was capable of predicting the pore structures of grain bulks, which provided a base for geometrically constructing airflow paths through the pore space between particles. The tortuosity for the widest and narrowest airflow paths predicted based on the discrete element model was in good agreement with the experimental data reported in the literature. Both pore-scale models (branched path and network) proposed in this study for predicting airflow resistance (pressure drop) through grain bulks appeared promising. The predicted pressure drop by the branched path model was slightly (<12%) lower than the experimental value, but almost identical to that recommended by ASABE Standard. The predicted pressure drop by the network model was also lower than the measured value (2.20 vs. 2.44 Pa), but very close to that recommended by ASABE Standard (2.20 vs. 2.28Pa).
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