A continuous random walk approach for stochastic modeling of particles dispersion and deposition using LES

A stochastic continuous random walk approach (CRW) method is used to model the subgrid-scale (SGS) velocity fluctuations seen by particles for large-eddy simulation of particle-laden flow. An Eulerian-Lagrangian approach was used for particles with the range of Stokes numbers from St = 1 to 24. First, particle statistics are reported where the filtered direct-numerical simulation (FDNS) velocity is used in the Lagrangian equations of solid particles without a subgrid-scale velocity fluctuation model. The DNS data are filtered by applying a sharp spectral filter to the turbulent velocity field. Comparative analysis of particulate phase results before and after filtering revealed a significant impact of SGS velocity fluctuations on particle dispersion and deposition within the channel. Subsequently, SGS fluctuations generated by the stochastic CRW model were added to the filtered velocity in the Lagrangian equation of particles. With the inclusion of a drift term and a proper Lagrangian time scale in the CRW equation, the method can accurately predict particle statistics. The particle deposition velocities for the range of Stokes number are validated against experimental data and DNS simulations. The results showed that the appropriate stochastic CRW model could correctly predict the SGS velocity fluctuations and enhance the accuracy of the LES of turbulent particle-laden flows.