Conditional Eulerian and Lagrangian velocity increment statistics of fully developed turbulent flow
Holger Homann, Daniel Schulz, Rainer Grauer

TL;DR
This study uses high-resolution simulations to analyze how conditioning on energy dissipation and vorticity affects velocity increment statistics in turbulent flows, revealing near-Gaussian distributions and improved scaling behavior.
Contribution
It introduces a novel conditioning method for Lagrangian velocity increments that reduces intermittency and enhances the inertial range scaling in turbulence statistics.
Findings
Conditioned PDFs are close to Gaussian across scales.
Conditioning reduces scale dependence of Lagrangian increment PDFs.
New conditioning approach further decreases intermittency in turbulence.
Abstract
Conditional statistics of homogeneous isotropic turbulent flow is investigated by means of high-Reynolds number direct numerical simulations performed with collocation points. Eulerian as well as Lagrangian velocity increment statistics under several conditions are analyzed and compared. In agreement with experimental data longitudinal probability density functions conditioned on a scale-averaged energy dissipation rate are close to Gaussian distributions over all scales within the inertial range of scales. Also transverse increments conditioned on either the dissipation rate or the square of the vorticity have quasi-Gaussian probability distribution functions (PDFs). Concerning Lagrangian statistics we found that conditioning on a trajectory averaged energy-dissipation rate significantly reduces the scale dependence of the…
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