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Evaluation of hydrodynamic behavior of urea granules in a pseudo-2D fluidized bed using drag models and comparison with PIV technique
Univ Teknol PETRONAS, CO2 Res Ctr CO2RES, Dept Chem Engn, Bandar Seri Iskandar 32610, Perak, Malaysia..
Univ Teknol PETRONAS, CO2 Res Ctr CO2RES, Dept Chem Engn, Bandar Seri Iskandar 32610, Perak, Malaysia..
Otto Von Guericke Univ, Inst Fluid Dynam & Thermodynam ISUT, Lab Fluid Dynam & Tech Flows LSS, Univ Pl 2, D-39106 Magdeburg, Germany..
Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences. Örnskoldsvik AB, MoRe Res, S-89122 Örnskoldsvik, Sweden.
2022 (English)In: Powder Technology, ISSN 0032-5910, E-ISSN 1873-328X, Vol. 406, article id 117578Article in journal (Refereed) Published
Abstract [en]

The urea fluidized bed hydrodynamics were simulated using computational fluid dynamics (CFD) vs. image processing technique. To identify the suitable model, sensitivity analyses on time step, number of nodes, and drag force coefficient were performed, and accordingly, Gidaspow and Syamlal-O & PRIME;Brien drag models were selected to simulate the fluidized bed for -particles categorized under Geldart-D. The CFD data were validated against the determined particle velocity using an image processing technique. Results indicate that Gidaspow model predictions for particles velocity and granular temperature are in good agreement whereas the Syamlal-O'Brien model resulted in underestimated predictions. Further analysis using Gidaspow model, the particle velocity increased by 12.5%, when the air inlet velocity is increased from 2 to 3 m/s and decreased by 87.5% when the particle sizes are changed from 2 to 4 mm. Although the primary loading height and pressure showed no effect, but at high pressures, it is important to consider humidity to avoid the negative impact on the granulation performance.

Place, publisher, year, edition, pages
2022. Vol. 406, article id 117578
Keywords [en]
CFD, Drag model, Eulerian simulation, Fluidized bed, PIV technique
National Category
Water Engineering
Identifiers
URN: urn:nbn:se:miun:diva-45335DOI: 10.1016/j.powtec.2022.117578ISI: 000809762400002Scopus ID: 2-s2.0-85131404142OAI: oai:DiVA.org:miun-45335DiVA, id: diva2:1675868
Available from: 2022-06-23 Created: 2022-06-23 Last updated: 2022-06-23Bibliographically approved

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