An effective three-marker drag model via sub-grid modeling for turbulent fluidization

• Published in: Chemical engineering science 2018-12, Vol.192, p.759-773
• Main Authors: Zhu, Li-Tao, Liu, Yuan-Xing, Luo, Zheng-Hong
• Format: Article
• Language: English
• Subjects: computational fluid dynamics; Effective drag correlation; Granular flow; Inhomogeneity; Sub-grid modelling; Turbulent fluidization
• ISSN: 0009-2509; 1873-4405
• DOI: 10.1016/j.ces.2018.08.026

[Display omitted] •An effective three-marker drag model is developed for considering the meso-scale effect on the hydrodynamic predictions.•The effect of uniform drag inputs on the derived three-marker drag correlation is quantified.•A comprehensive comparison between several typical sub-grid models and present work is implemented.•Coarse-grid validation reveals that the developed model can significantly improve hydrodynamic predictions. The effect of meso-scale structures on hydrodynamic predictions is not considered in the classically uniform drag models when the coarse grid is used. To address this issue, this study tries to develop an effective three-marker drag correlation via straightforward sub-grid modeling, which accounts for a parabolic spatial concentration distribution within a computational grid. The reliability and accuracy of the developed model is then assessed in detail. How the uniform drag inputs affect the derived sub-grid correction is quantified for the first time. Besides, a comprehensive comparison between several typical sub-grid models and present work is implemented. Results reveal a systematic dependence of our drag modification on the concentration gradient as an additional marker. Coarse-grid hydrodynamic validation shows that the developed model yields a fairly improved agreement with experiments under various operating conditions in a 3D turbulent fluidized bed. Furthermore, results demonstrate that the present model using different uniform drag inputs still can exhibit satisfactory performance. The developed model is able to resolve the heterogeneous flow behavior both cheaply and adequately, which is potentially applied for industrial reactor design and optimization.