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Studies of grain segregation patterns on a Destoner using a CFD-DEM approach

Ananda Subramani Kannan (Institutionen för tillämpad mekanik, Strömningslära) ; Michael Adsetts Edberg Hansen ; Jens Michael Carstensen ; Peter Thorn ; Jacob Lund ; Srdjan Sasic (Institutionen för tillämpad mekanik, Strömningslära)
8th International Conference on Computational and Experimental Methods in Multiphase and Complex Flow (2015)
[Konferensbidrag, refereegranskat]

Removal of contaminants from ‘food grade’ quality grains is of great importance in food and grain processing operations. A thorough understanding of the inherent granular segregation profiles on this processing equipment is a pivotal step in the design and development of more efficient processes. One such grain cleaning operation is the ‘density-based separation’ using a destoner. This process removes stones and other heavy material from lighter food grains using a vibrating deck and fluidizing air. In this paper we formulate a CFD-DEM framework (set up and implemented in the OpenFOAM® environment) to study granular segregation patterns on a destoner. The scheme is first validated by comparing simulations with experimental data using a gas-solid fluidized-bed test case. A good agreement between the experiments and the simulations is noted. This proposed framework is then used to characterize the combined effects of deck inclination and fluidization velocities on the separation profiles generated from a virtual destoner. We have found these profiles to be highly sensitive to changes in fluidization conditions, with the gradual development of segregation zones at velocities close to the minimum fluidization velocity of the heavier component. A deck inclination of 5 degrees and a fluidization velocity of 2.0 m/s is considered optimal while steeper slopes (inclinations of 15 degrees) and lower air velocities (0 and 1.5 m/s) are deemed unsuitable for segregation.

Nyckelord: Destoner, Grain cleaning operation, OpenFOAM®, CFD-DEM, Fluidization



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Denna post skapades 2015-05-12.
CPL Pubid: 217012