Improved Discrete Random Walk Model for Turbulent Tracking of Particle Transport

SREEKESH KOOKKAL, Suresh Dhaniyala, Clarkson University

     Abstract Number: 553
     Working Group: Aerosol Physics

Abstract
The transport of inertial particles in turbulent flow can be solved using a stochastic model, where the instantaneous particle velocity is calculated from the mean velocity and the instantaneous turbulent velocity fluctuation. In the DRW model, the fluctuating component of velocity is treated as the discrete piecewise, the constant function of time. Earlier studies with commercial computational fluid dynamics (CFD) software such as FLUENT, have shown that particle transport loss due to turbulence is often over-predicted with the built-in Discrete Random Walk (DRW) model. This over-prediction also impacts the accuracy of particle concentration predictions in the bulk flow, resulting in erroneous calculations of particle concentrations in scenarios such as in the flow downstream of nozzles and orifices. We developed a DRW model for use with FLUENT that improves the accuracy of particle transport in k-ϵ and SST k-ω turbulence models. We use channel flow simulations conducted for a bulk Reynolds number 2280 and a non-dimensional relaxation time varied from 0.01 to 25 to evaluate our model. We will present a comparison of particle transport statistics such as concentrations and mean and RMS particle velocity for different DRW models with the Direct Numerical Simulation (DNS) data.