Multiscale correlations and conditional averages in numerical turbulence

Siegfried Grossmann, Detlef Lohse, Achim Reeh

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)
64 Downloads (Pure)

Abstract

The equations of motion for the nth order velocity differences raise the interest in correlation functions containing both large and small scales simultaneously. We consider the scaling of such objects and also their conditional average representation with emphasis on the question of whether they behave differently in the inertial or the viscous subranges. The turbulent flow data are obtained by Navier-Stokes solutions on a 603 grid with periodic boundary conditions and Reλ=70. Our results complement previous high Re data analysis based on measured data [A. L. Fairhall, V. S. L'vov, and I. Procaccia, Europhys. Lett 43, 277 (1998)] whose preference were the larger scales, and the analysis of both experimental and synthetic turbulence data by [R. Benzi and co-workers, Phys. Rev. Lett. 80, 3244 (1998); Phys. Fluids 11, 2215 (1999)]. The inertial range fusion rule is confirmed and insight is obtained for the conditional averages (the local dissipation rate conditioned on the velocity fluctuations).
Original languageEnglish
Article number5195
Number of pages11
JournalPhysical review E: Statistical physics, plasmas, fluids, and related interdisciplinary topics
Volume61
Issue number5
DOIs
Publication statusPublished - 2000

Keywords

  • METIS-129577
  • IR-24776

Fingerprint Dive into the research topics of 'Multiscale correlations and conditional averages in numerical turbulence'. Together they form a unique fingerprint.

Cite this