Assessment against DNS data of a coupled CFD - stochastic model for particle dispersion in turbulent channel flows

The accurate prediction of particle transport is a primary safety issue. Tracking particles in Lagrangian fashion can naturally be performed with CFD tools which provide the right framework to follow the paths of particles in complex geometries. The presence of turbulent structures in the fluid complicates the particle tracking problem considerably, because particle trajectories are no longer deterministic and additional modeling of the velocity fluctuations is needed. In the present investigation, a Lagrangian continuous random walk (CRW) model is developed to predict turbulent particle dispersion in wall-bounded flows with prevailing inhomogeneous turbulence. The particle model uses 3D mean flow data from the Fluent CFD code, as well as Eulerian statistics from Direct Numerical Simulation (DNS) databases. The turbulent fluid velocities are based on the non-dimensional Langevin equation. The model predictions are compared to the DNS data by Marchioli et al. (2007) who produced detailed statistics of velocity and transfer rates for classes of particles having Stokes numbers between 0.2 and 125 and dispersed in a parallel channel flow with Reτ=150. The model is in very good agreement with the DNS data for the various measures of particle dispersion. The predicted deposition rates are also in good agreement with the widely used experimental correlation of McCoy and Hanratty (1977) and Liu and Agarwal (1974).