Scale-dependent statistics of inertial particle distribution in high Reynolds number turbulence

Keigo Matsuda, Kai Schneider, and Katsunori Yoshimatsu
Phys. Rev. Fluids 6, 064304 – Published 9 June 2021

Abstract

Multiscale statistical analyses of inertial particle distributions are presented to investigate the statistical signature of clustering and void regions in particle-laden incompressible isotropic turbulence. Three-dimensional direct numerical simulations of homogeneous isotropic turbulence at high Reynolds number (Reλ200) are performed. Lagrangian motion of inertial particles are tracked by the one-way coupled point-particle method assuming the Stokes drag. Up to 109 inertial particles for each Stokes number ranging from 0.01 to 5.0 are computed. Orthogonal wavelet analysis is then applied to the computed particle-number density fields. Scale-dependent skewness and flatness values of the particle-number density distributions are calculated and the influence of Reynolds number Reλ and Stokes number St is assessed. For St1, both the scale-dependent skewness and flatness values become larger as the scale decreases, suggesting intermittent clustering at small scales. For St0.2, the flatness at intermediate scales, i.e., scales larger than the Kolmogorov scale and smaller than the integral scale of the flow, increases as St increases, and the skewness exhibits negative values at the intermediate scales. The negative values of the skewness are a signature of void regions. These results indicate that void regions at the intermediate scales are pronounced and intermittently distributed for such small Stokes numbers. As Reλ increases, the flatness increases weakly. For Reλ328, the skewness shows negative values at large scales, suggesting that even for St1, void regions are pronounced at large scales, while clusters are pronounced at small scales.

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  • Received 20 July 2020
  • Accepted 17 May 2021

DOI:https://doi.org/10.1103/PhysRevFluids.6.064304

©2021 American Physical Society

Physics Subject Headings (PhySH)

Fluid Dynamics

Authors & Affiliations

Keigo Matsuda1,*, Kai Schneider2, and Katsunori Yoshimatsu3

  • 1Research Institute for Value-Added-Information Generation (VAiG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 236-0001, Japan
  • 2Institut de Mathématiques de Marseille (I2M), Aix-Marseille Université, CNRS and Centrale Marseille, 39 Rue F. Joliot-Curie, 13453 Marseille Cedex 13, France
  • 3Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya 464-8601, Japan

  • *k.matsuda@jamstec.go.jp

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Issue

Vol. 6, Iss. 6 — June 2021

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