Journal
POWDER TECHNOLOGY
Volume 413, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.powtec.2022.118036
Keywords
Dense dispersed gas -solid flow; Dense discrete phase model (DDPM); Agglomeration modeling; Drag model; Industrial -scale cyclone; Kinetic theory of granular flow (KTGF)
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The Dense Discrete Phase Model coupled with an agglomeration model is developed and validated for the simulation of industrial cyclones with high solid loads. The performance of the model is influenced by sub-models, model parameters, and numerical parameters. A sensitivity analysis was conducted to optimize the model's performance, identifying the turbulence model and particle-particle restitution coefficient as having the strongest influence. The study recommends a set of sub-models, model parameters, and numerical parameters for accurately predicting the hydrodynamics of large-scale highly loaded cyclones.
The Dense Discrete Phase Model coupled with an agglomeration model is developed and validated for the simulation of industrial cyclones with high solid loads. The performance of the model is influenced by sub -models, model parameters, and numerical parameters. To optimize the performance of the present CFD model, an extensive sensitivity analysis was performed, varying one sub-model or parameter at a time, and systematically assessing the effect on the results through comparisons with measured pressure drop and sepa-ration efficiency of a highly loaded pilot-scale cyclone. The investigation shows that the turbulence model and particle-particle restitution coefficient have the strongest influence. This study concludes with the recommen-dation of a set of sub-models, model parameters, and numerical parameters providing the best prediction of the hydrodynamics of large-scale highly loaded cyclones. In addition, the impact of some operating conditions on the performance of a large-scale highly loaded cyclone were examined.
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