Direct numerical simulation of decaying compressible turbulence and shocklet statistics

Ravi Samtaney, D. I. Pullin, Branko Kosović

Research output: Contribution to journalArticlepeer-review

315 Scopus citations

Abstract

We present results from 1283 and 2563 direct numerical simulations (DNS) of decaying compressible, isotropic turbulence at fluctuation Mach numbers of Mt ˜0.1-0.5 and at Taylor Reynolds numbers Reλ = O(50-100). The presence or absence of fluctuations of thermodynamic quantities as well as velocity divergence in the initial conditions are found to have a negligible effect on the decay of turbulent kinetic energy. The decay of the turbulent kinetic energy shows no significant effect of Mt and power laws fitted to the timewise decay exhibit exponents n = 1.3-1.7 that are similar to those found for decaying incompressible turbulence. The main new phenomenon produced by compressibility is the appearance of random shocklets which form during the main part of the decay. An algorithm is developed to extract and quantify the shocklet statistics from the DNS fields. A model for the probability density function (PDF) of the shocklet strength Mn - I (Mn is the normal shock Mach number) is derived based on combining weak-shock theory with a model of the PDF of longitudinal velocity differences in the turbulence. This shows reasonable agreement with PDFs obtained from the shocklet extraction algorithm. The model predicts that at moderate Mt the most probable shocklet strength is proportional to Mt/Reλ1/12 and also that the PDF for the shock thicknesses has an inverse cubic tail. The shock thickness statistics are found to scale on the Kolmogorov length rather than the mean free path in the gas.

Original languageEnglish (US)
Pages (from-to)1415-1430
Number of pages16
JournalPhysics of Fluids
Volume13
Issue number5
DOIs
StatePublished - May 2001
Externally publishedYes

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes
  • Computational Mechanics

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