On the error estimate in sub-grid models for particles in turbulent flows

The use of Large Eddy Simulation (LES) has emerged in recent years as a powerful simulation technique with the specific goal of achieving a good statistical accuracy while retaining a computational cost lower than Direct Numerical Simulations (DNS) [1]. In LES, only large-scale motions are directly computed (resolved on the computational grid) while small scale motions are not computed explicitly but modeled via Sub-Grid Scale (SGS) models. Due to the complex statistical properties of turbulence, many models and methodologies have been proposed in the past. Although none of the proposed models can be considered a perfect substitute to DNS, their performance can be sometimes considered fairly accurate for what concerns the most common Eulerian turbulent flow statistics. The problem of particle transport in turbulence demands much more to LES than just reproducing low order Eulerian statistics (e.g. spectra, average profiles etc) [2, 3]. Here we propose a way to quantify the effect of (the error due to) sub-grid modeling on particle properties