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Large-Eddy Simulations (LES) of two-phase turbulent flows exhibitquantitative differences in particle statistics if compared to Direct NumericalSimulations (DNS) which, in the context of the present study, is considered theexact reference case. Differences are primarily due to filtering, a fundamentalintrinsic feature of LES. Filtering the fluid velocity field yields approximatecomputation of the forces acting on particles and, in turn, trajectories thatare inaccurate when compared to those of DNS. In this paper, we focus preciselyon the filtering error for which we quantify a lower bound. To this aim, we usea DNS database of inertial particle dispersion in turbulent channel flow and weperform a-priori tests in which the error purely due to filtering is singledout removing error accumulation effects, which would otherwise lead toprogressive divergence between DNS and LES particle trajectories. By applyingfilters of different type and width at varying particle inertia, wecharacterize the statistical properties of the filtering error as a function ofthe wall distance. Results show that filtering error is stochastic and has anon-Gaussian distribution. In addition, the distribution of the filtering errordepends strongly on the wall-normal coordinate being maximum in the bufferregion. Our findings provide insight on the effect of subgrid-scale velocityfield on the force driving the particles, and establish the requirements whicha LES model must satisfy to predict correctly the velocity and the trajectoryof inertial particles.

Intrinsic filtering errors of Lagrangian particle tracking in LES flow fields