A study of the performance of pilot scale gravity sorters using a CFD-DEM computational framework

Other conference contribution, 2016

Gravity sorters are utilized in the downstream processing of harvested grains in order to clean and enhance the grain quality for human consumption. In this paper, we undertake a detailed assessment into the performance of such sorters using a coupled CFD-DEM framework implemented in the OpenFOAM® environment. We look to establish and characterize the performance of gravity sorters cleaning harvested wheat at different operating conditions such as: deck tilt, fluidization conditions, deck vibrational intensity etc. Our simulations result in the identification of the optimal deck tilt and consequently the corresponding fluidization velocity and deck vibration intensity required for obtaining peak performance. A clear segregation between the light wastes present in the feed and the good product is noted in the virtual sorter, with the separation becoming poorer at steeper deck tilts. Finally, a regression model relating the operating conditions to the performance is developed in order to aid in making qualified guesses during the startup of such sorters.