This paper presents large eddy simulation (LES) of polydispersed turbulent recirculating flows using a two-way coupled probability density function of the population balance equation (PDF-PBE). A stochastic Monte Carlo method is adopted to solve the PDF-PBE on an ensemble of notional Lagrangian particles and the method of Stokes binning, that was recently developed by Salehi et al. (2017) is employed to explicitly treat effects of inertia. The PDF-PBE is applied to the experiment of Boŕee et al. (2001) which studied dispersion of polysized inertial particles in a bluff body configuration. The particle mass loading is 22% where the dispersed elements affect the carrier phase velocity. The simulations are performed using both the standard Smagorinsky and the Wall-Adapting Local Eddy-viscosity (WALE) subgird turbulent models. It is found that the subgrid model has a significant impact on the results, particularly on the carrier velocity. The WALE model shows a better agreement with the measurements. Different boundary conditions are tested for injection of notional particles. It is demonstrated both dispersed and carrier phase velocities are initially sensitive to the particle boundary condition whereas the difference between tested conditions becomes marginal further downstream. The best results are obtained for the particle boundary condition that accounts for effects of inertia at the inlet. Finally, the sensitivity of the PDF-PBE simulations to the number of Stokes bins is studied. It is found that eight Stokes bins are enough to accurately model the polysized particles dispersion in a bluff body configuration. The results indicate that particle dispersion is notably sensitive to the number of Stokes bins but the particle velocity predictions are much less sensitive with small variation in velocity results over the range of Stokes bins that were tested.
|Number of pages||13|
|Journal||International Journal of Heat and Fluid Flow|
|Publication status||Published - Jun 2020|
- Large eddy simulation (LES)
- Population balance equation (PBE)
- Stochastic Lagrangian