A stochastic model for particle motion in large-eddy simulation

Abstract

Most of the studies on large-eddy simulation (LES) of particle-laden flows assume that the effect of subgrid scales on the particle motion is negligible. This assumption may break down, particularly when particles have a small time constant and/or the filtered energy is significant. In this work, a stochastic model is proposed for the particle motion in LES while considering the effect of subgrid fluctuations. The model assumes that the fluid particle seen by the heavy particle evolves based on a diffusion stochastic process. For model assessment, both a priori and a posteriori tests are conducted for a particle-laden decaying isotropic turbulence. In the a priori test the filtered velocity field, obtained via filtering the DNS velocities, and in the a posteriori test the LES velocity field, obtained via the dynamic Smagorinsky model, are applied to particles through the stochastic model. The small-particle statistics obtained through the stochastic model very well match those obtained through DNS in the a priori test, once the effects of the initial conditions have decayed. There is also a good agreement with DNS results in the a posteriori test. It is shown that the neglect of subgrid fluctuations is not acceptable for these cases. For large particle time constants, the model needs to be adjusted.