Comprehensive validation analysis of sub-grid drag and wall corrections for coarse-grid two-fluid modeling

• Published in: Chemical engineering science Vol. 196; pp. 478 - 492
• Main Authors: Zhu, Li-Tao, Rashid, Taha Abbas Bin, Luo, Zheng-Hong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 16-03-2019
• Subjects: Computational fluid dynamics; Gas-particle fluidization; Sub-grid model; Two-fluid modelling; Validation; Wall correction; Validation; Sub-grid model; Gas-particle fluidization; Computational fluid dynamics; Two-fluid modelling; Wall correction
• ISSN: 0009-2509; 1873-4405
• DOI: 10.1016/j.ces.2018.11.026

•A comprehensive validation study of the developed model to its predictability is conducted.•The computed results accord with the experimental data well over various flow regimes.•The computation efficiency via the developed sub-grid model can be significantly improved.•To capture the macroscopic flow features reasonably, an additional wall correction is not needed for the developed model.
Development and validation of sub-grid models are of pivotal importance for coarse-grid two-fluid modeling of gas-particle fluidization. In prior study (Zhu et al., 2018, Chem. Eng. Sci. 192, 759–773), we developed an effective three-marker sub-grid drag model to consider the local heterogeneity in gas-particle flows. In this study, we perform a comprehensive 3D hydrodynamic validation analysis of the developed model to its predictability. Specifically, the validation covers more flow situations with respect to rapid, turbulent and bubbling fluidization. Besides, we introduce a simplified wall correction factor for assessing how the bounding walls impact on flow hydrodynamics. Computational results accord well with the experimental data over various flow regimes. The developed model can adequately capture the macroscopic flow properties without an additional wall modification. Compared with the fine-grid two-fluid modeling using the uniform drag model for a lab-scale riser, approximately 44 times speedup in computational time is achieved via the developed model. A much more significant reduction in computational time can be consequently expected for industrial-scale reactors.