Inertial particle distribution in high Reynolds number turbulence: wavelet-based scale-dependent statistics

The nonlinear dynamics of inertial particles in high Reynolds number turbulence, and in particular particle clustering, are important fundamental processes in atmospheric science. Here we analyze particle data from three-dimensional direct numerical simulations of particle-laden homogeneous isotropic turbulence at high Reynolds number, up to $Re_\lambda = 531$ and with up to $10^9$ particles. The influence of Reynolds and Stokes numbers on the multiscale clustering structure is investigated. To calculate scale-dependent statistics we apply orthogonal wavelet decomposition to the particle density fields. The intermittency of the density fields is quantified by computing scale-dependent flatness values. Negative values of the scale-dependent skewness allow to assess the spatial scale of void regions. We also show that the number of particles has some impact on high-order statistics, especially at small scales.