A structural subgrid-scale model for the collision-related statistics of inertial particles in large-eddy simulations of isotropic turbulent flows

Abstract

In large-eddy simulations of particle-laden isotropic turbulent flows, the collision of inertial particles is strongly influenced by missing small-scale turbulence. In this paper, we apply the Kinematic Simulation with Approximate Deconvolution (KSAD) model to determine the contribution of small-scale turbulence to the motion of inertial particles and improve the prediction accuracy of the radial distribution function (RDF) and radial relative velocity (RRV), which are closely related to particle collisions. Different values of Stokes numbers (St), which are defined as the ratio of the particle response time to the Kolmogorov time scale, are considered. The KSAD model significantly improves the prediction accuracy of the RRV for all considered St. For the prediction of RDF, good agreement between the KSAD model and direct numerical simulations is only observed for large St, i.e., St ≥ 2.0. To explore the reason for the poor prediction of the KSAD model for small St, we compare the Eulerian statistics of the flow fields and the Lagrangian properties of the particles from different simulations and find the key reason is that the Gaussian turbulence generated in the kinematic simulation model is inadequate in recovering the vortex centrifugal effect of small-scale turbulence on the inertial particle clustering at small St.