Abstract

An essential ingredient of turbulent flows is the vortex stretching mechanism, which emanates from the non-linear interaction of vorticity and strain-rate tensor and leads to formation of extreme events. We analyze the statistical correlations between vorticity and strain rate by using a massive database generated from very well resolved direct numerical simulations of forced isotropic turbulence in periodic domains. The grid resolution is up to $12288^3$, and the Taylor-scale Reynolds number is in the range $140-1300$. In order to understand the formation and structure of extreme vorticity fluctuations, we obtain statistics conditioned on enstrophy (vorticity-squared). The magnitude of strain, as well as its eigenvalues, is approximately constant when conditioned on weak enstrophy; whereas they grow approximately as power laws for strong enstrophy, which become steeper with increasing $R_\lambda$. We find that the well-known preferential alignment between vorticity and the intermediate eigenvector of strain tensor is even stronger for large enstrophy, whereas vorticity shows a tendency to be weakly orthogonal to the most extensive eigenvector (for large enstrophy). Yet the dominant contribution to the production of large enstrophy events arises from the most extensive eigendirection, the more so as $R_\lambda$ increases. Nevertheless, the stretching in intense vorticity regions is significantly depleted, consistent with the kinematic properties of weakly-curved tubes in which they are organized. Further analysis reveals that intense enstrophy is primarily depleted via viscous diffusion, though viscous dissipation is also significant. Implications for modeling are nominally addressed as appropriate.

Highlights

  • Small-scale intermittency, a hallmark of fluid turbulence, refers to the occurrence of sudden and intense fluctuations of velocity gradients [1,2], as routinely reflected in long tails of their strongly non-Gaussian probability distributions [3,4,5,6]

  • We analyze the statistical correlations between vorticity and strain rate by using a massive database generated from very well-resolved direct numerical simulations of forced isotropic turbulence in periodic domains

  • We have systematically investigated the statistical correlations underlying the vortex stretching mechanism in direct numerical simulations of stationary isotropic turbulence across a wide range of Reynolds numbers (140 Rλ 1300)

Read more

Summary

INTRODUCTION

Small-scale intermittency, a hallmark of fluid turbulence, refers to the occurrence of sudden and intense fluctuations of velocity gradients [1,2], as routinely reflected in long tails of their strongly non-Gaussian probability distributions [3,4,5,6]. The mechanisms of vortex stretching may differ significantly between such regions In this regard, statistics conditioned on the strength of vorticity or strain offer the unique prospect of understanding how small-scale structures are produced by the flow, by isolating the extreme events from the moderate and the weak events. Our objective is to present a detailed fundamental investigation of turbulence small-scale structure in light of vortex stretching and resulting enstrophy production. To this end, we utilize pseudospectral DNS of isotropic turbulence in a periodic domain, which is the most efficient numerical tool to study the small-scale properties of turbulence. Some details on numerical resolution, crucial in the study of small-scale turbulent statistics, are presented in Appendix

NUMERICAL APPROACH AND DATABASE
VORTICITY AND STRAIN CORRELATIONS
Alignment
Strain and eigenvalues
Enstrophy production
Viscous destruction of enstrophy
Findings
CONCLUSIONS

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.