Vorticity Statistics and the Time Scales of Turbulent Strain

TL;DR

This paper investigates the statistical properties of turbulent strain and vorticity, revealing that vorticity intermittency modifies traditional strain time-scale estimates through heuristic closure hypotheses and numerical data analysis.

Contribution

It introduces a novel approach linking vorticity and strain statistics using closure hypotheses and numerical simulations, refining turbulence time-scale estimates.

Findings

Strain persistence times are derived from Lagrangian eigenvalue correlations.

Vorticity intermittency influences the strain time-scale estimates.

Heuristic closure hypotheses connect vorticity and strain statistics.

Abstract

Time scales of turbulent strain activity, denoted as the strain persistence times of first and second order, are obtained from time-dependent expectation values and correlation functions of lagrangian rate-of-strain eigenvalues taken in particularly defined statistical ensembles. Taking into account direct numerical simulation data, our approach relies on heuristic closure hypotheses which allow us to establish a connection between the statistics of vorticity and strain. It turns out that softly divergent prefactors correct the usual "1/s" strain time-scale estimate of standard turbulence phenomenology, in a way which is consistent with the phenomenon of vorticity intermittency.