Semi-resolved CFD–DEM for thermal particulate flows with applications to fluidized beds

• Published in: International journal of heat and mass transfer Vol. 159; p. 120150
• Main Authors: Wang, Zekun, Liu, Moubin
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-10-2020; Elsevier BV
• Subjects: CFD–DEM; Computational fluid dynamics; Fluid flow; Fluid-particle two-phase flow; Fluidized bed; Fluidized bed reactors; Fluidized beds; Free convection; Heat exchange; Momentum; Particulate flows; Semi-resolved CFD–DEM; Temperature distribution; Thermal convection; Three dimensional models; Three dimensional printing; Turbulence effects; Turbulence models; Vorticity; CFD–DEM; Thermal convection; Particulate flows; Fluid-particle two-phase flow; Semi-resolved CFD–DEM; Fluidized bed
• ISSN: 0017-9310; 1879-2189
• DOI: 10.1016/j.ijheatmasstransfer.2020.120150

•Semi-resolved CFD–DEM is extended to particulate flows with thermal convection.•Background fluid properties are corrected using kernel-based approximation.•Model A is adopted to address fluid-particle interaction with more force models.•Turbulence model is incorporated into the semi-resolved CFD–DEM.•The semi-resolved CFD–DEM provides better predictions and more details in modeling thermal particulate flows in fluidized bed.•Several phenomena observed in thermal fluidized bed are discussed.
Particulate flows with heat transfer widely exist in industry including fluidized bed reactor and powder-based 3D printing, and are frequently modeled with CFD–DEM coupled approaches. Recently, we developed a semi-resolved CFD–DEM approach, which bridges the simulation gap between the resolved and unresolved CFD–DEM (Wang et al., 2019). The semi-resolved CFD–DEM is as efficient as the conventional unresolved CFD–DEM and as accurate as the resolved CFD–DEM, while it is validated for particulate flows with momentum exchange with Model B without heat exchange. In this paper, we further extend the semi-resolved CFD–DEM approach to model particulate flows with momentum exchange and thermal convection. Firstly, similar to background fluid velocity, background fluid temperature is corrected through kernel-based approximations on the neighboring fluid cells rather than simply taking values in the local cell containing the concerned particle. Secondly, Model A is adopted in the semi-resolved CFD–DEM, leading to more powerful capabilities in handling complicated flows. Force models like the Magnus force, virtual mass force are also included. Thirdly, turbulence model is incorporated into the semi-resolved CFD–DEM approach to address possible turbulence effects. Finally, the developed semi-resolved CFD–DEM is applied to modeling the complex particulate flows in fluidized bed. The obtained numerical results are compared with experimental data and results from other sources. It is demonstrated that the present semi-resolved CFD–DEM is effective in modeling particulate flows with thermal convection. Compared to the conventional unresolved CFD–DEM, this semi-resolved CFD–DEM can provide better predictions and more details on particle temperature distribution, mean temperature, solid/fluid fraction, velocity autocorrelation and vorticity field.