Abstract
CFD-DEM (computational fluid dynamic-discrete element method) is a promising approach for simulating fluid–solid flows in fluidized beds. This approach generally under-predicts the granular temperature due to the use of drag models for the average drag force. This work develops a simple model to improve the granular temperature through increasing the drag force fluctuations on the particles. The increased drag force fluctuations are designed to match those obtained from PR-DNSs (particle-resolved direct numerical simulations). The impacts of the present model on the granular temperatures are demonstrated by posteriori tests. The posteriori tests of tri-periodic gas–solid flows show that simulations with the present model can obtain transient as well as steady-state granular temperature correctly. Moreover, the posteriori tests of fluidized beds indicated that the present model could significantly improve the granular temperature for the homogenous or slightly inhomogeneous systems, while it showed negligible improvement on the granular temperature for the significantly inhomogeneous systems.
Highlights
IntroductionFluidized beds with fluid (gas/liquid)–solid flows are operating units adopted in chemical and energy processes
Fluidized beds with fluid–solid flows are operating units adopted in chemical and energy processes
computational fluid dynamic (CFD)-DEM simulations of gas–solid flows suspended in a tri-periodic domain were performed over a wide range of solid volume fractions (0.1 ≤ φ ≤ 0.4), Reynolds numbers (10 ≤ Re ≤ 100), and density ratios (100 ≤ ρs /ρ f ≤ 2000)
Summary
Fluidized beds with fluid (gas/liquid)–solid flows are operating units adopted in chemical and energy processes. Yu et al [16] recently reported that it is necessary to consider the fluctuations of the meso-scale drag force to attain correct granular temperature in coarse-grid CFD-DEM simulations. Akiki et al [17] found that the individual drag is dependent on the local structures of neighboring particles, and they proposed a pairwise interaction extended point-particle model for the prediction of the drag force. The obtained drag force difference in the cells in CFD-DEM could be magnified to match the correct magnitude of drag force difference Following this idea, in this paper, a simple model is proposed to improve the granular temperatures through enlarging the existent drag force difference on individual particles in the same computational cell.
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