Comparison of Experimental Results from Operating a Novel Fluidized Bed Classifier with CFD Simulations Applying Different Drag Models and Model Validation

نویسندگان

چکیده

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

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ژورنال

عنوان ژورنال: Processes

سال: 2022

ISSN: ['2227-9717']

DOI: https://doi.org/10.3390/pr10091855