Scale-dependent divergence of inertial particle velocity in isotropic turbulence

Clustering of inertial particles in high Reynolds number turbulence is an important fundamental process, e.g., for raindrop formation in atmospheric clouds. The particle concentration has multiscale clusters and voids owing to the multiscale nature of turbulence. Recently, Matsuda et al. (Phys. Rev. Fluids, 2021) showed the cluster/void pronounced structures of inertial particle clustering depend on the scale and the Stokes number. Hence, to get insight into the multiscale dynamics of particle clustering, we analyze the scale dependence of cluster formation/destruction, which is quantified by negative/positive divergence values of particle velocity, respectively.

The inertial particle distribution data are obtained from the direct numerical simulation of particle-laden homogeneous isotropic turbulence (Matsuda et al., 2021). The Lagrangian particle motion is modeled based on the Stokes drag. The particle velocity divergence is calculated based on the temporal rate of change in volumes configured by a tessellation technique (Oujia et al., J. Fluid Mech., 2020). The scale-dependence analysis based on a multi-resolution technique is applied to the velocity divergence data on unstructured discrete particle positions, and the results from this analysis will be discussed.