Abstract
A cold-flow lab-scale cross-flow fluidized bed classifier was simulated using the CFD software Barracuda VR®. The purpose of the study was to identify the most suitable drag model and make the model adjustments that provide the best representation of the flow situation in the classifier when comparing the results with the experimental data. Two particle types were used in the simulations and in the experiments: zirconia (median diameter 69 µm, skeletal density 3830 kg/m3) and steel (290 µm, 7790 kg/m3). Ten different cases, with different solids loading values, were investigated: three with pure zirconia particles, three with pure steel particles, and four with a mixture of zirconia (28%) and steel (72%). Several different drag models were tried out in the simulations. However, none of the available models were able to predict the classification efficiency observed in experiments with their default settings. Although most of the drag models correctly predicted the inversely proportional behavior of the classification efficiency vs. solids loading, the classification efficiency was overpredicted. It was observed that a combined WenYu/Ergun drag model gave a wide range of accuracy, by being able to capture the behavior of both dense and dilute particle systems. Even though the predictions of the classification efficiency for steel particles were acceptable, a larger deviation was observed with Geldart A zirconia particles. CFD simulations with the WenYu and Ergun combined drag model were used for further validation against the experimental observations. In this case, previously published experimental data for fluidization of pure Zirconia particles were used. The fluidization of zirconia was modelled in Barracuda VR® with adjustment of the combined WenYu/Ergun drag model parameter (k1), to obtain a suitable validation. Furthermore, the effect of adding the blended acceleration model (BAM) for the fluidization simulations is discussed. It was observed that the fixed bed pressure drop was very accurate compared to the experimental observation, but the pressure drop after the fluidization was slightly overpredicted.
Funder
The Research Council of Norway
GE Carbon Capture
Subject
Process Chemistry and Technology,Chemical Engineering (miscellaneous),Bioengineering
Cited by
3 articles.
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