A priori and a posteriori analysis of models for Large-Eddy simulation of particle-laden flow

TL;DR

This paper evaluates and compares three models for Large-Eddy simulation of particle-laden flows, analyzing their accuracy in predicting particle dispersion and turbulence effects through a priori and a posteriori methods.

Contribution

It provides a comprehensive quantitative comparison of ADM and stochastic models for particle-laden flow simulation at different Stokes numbers.

Findings

ADM improves statistical accuracy but mispredicts dispersion at high Stokes numbers.

Stochastic models perform well at small Stokes numbers with proper parameters.

Neglecting small-scale effects may be preferable at high Stokes numbers.

Abstract

In Large-Eddy simulation of particle-laden flow, the effect of the unresolved scales on the particles needs to be modelled. In this work we analyse three very promising models, namely the approximate deconvolution method (ADM) which was proposed for particle-laden flow independently by Kuerten (Phys. Fluids 18, 2006) and Shotorban and Mashayek (Phys. Fluids 17, 2005) and two stochastic models, proposed by Shotorban and Mashayek (J. Turbul. 7, 2006) and Simonin et al. (Appl. Sci. Res. 51, 1993). We present results from a priori and a posteriori analysis of these models in isotropic turbulence at Re_lambda=52. This data allows for a direct quantitative comparison of the models. The analysis shows that ADM always leads to improved statistics but that even for high Stokes numbers, the rate of dispersion is not predicted correctly by ADM. Concerning the stochastic models, we found that with the correct choice of model parameters, the models perform well at small Stokes numbers. On the other hand, at high Stokes numbers the stochastic models show significant errors such that it may be recommendable to neglect the small scale effects instead of using one of the stochastic models.