Abstract

In this work, the two-point probability density function (PDF) for the velocity field of isotropic turbulence is modeled using the kappa distribution and the concept of superstatistics. The PDF consists of a symmetric and an anti-symmetric part, whose symmetry properties follow from the reflection symmetry of isotropic turbulence, and the associated non-trivial conditions are established. The symmetric part is modeled by the kappa distribution. The anti-symmetric part, constructed in the context of superstatistics, is a novel function whose simplest form (called “the minimal model”) is solely dictated by the symmetry conditions. We obtain that the ensemble of eddies of size up to a given length r has a temperature parameter given by the second order structure function and a kappa-index related to the second and the third order structure functions. The latter relationship depends on the inverse temperature parameter (gamma) distribution of the superstatistics and it is not specific to the minimal model. Comparison with data from direct numerical simulations (DNS) of turbulence shows that our model is applicable within the dissipation subrange of scales. Also, the derived PDF of the velocity gradient shows excellent agreement with the DNS in six orders of magnitude. Future developments, in the context of superstatistics, are also discussed.

Highlights

  • Isotropic turbulence is an idealized form of turbulence which is defined by the invariance of the scalar correlation functions of the velocity field under translation, rotation, and reflection [1,2]

  • The dependence of S and F on the Reynolds number is determined through direct numerical simulations of isotropic turbulence and is discussed below

  • We may say that the model acquires a greater regime of applicability as we look at cases of higher Reynolds numbers

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Summary

Introduction

Isotropic turbulence is an idealized form of turbulence which is defined by the invariance of the scalar correlation functions of the velocity field under translation, rotation, and reflection [1,2]. (ii) this relation does not depend on the model, only on the superstatistics gamma distribution; (iii) the DNS data and self-consistency imply that the theory is valid for r up to ~10η, where η is the previously mentioned Kolmogorov dissipation range scale; (iv) the PDF for the velocity gradient can be derived from the two-point PDF in the limit r→0 (for the minimal model) which agrees well within six orders of magnitude with the DNS data for that quantity; (v) on the theoretical side, the Karman-Howarth equation relating the second and third order structure function of isotropic turbulence translates into a differential equation relating the temperature parameter and the kappa index functions.

Structure Functions of Isotropic Turbulence
Two-Point Joint Probability Distribution for the Velocity Field
Transformation
Modeling the Symmetric Sector: κ-Distribution and Turbulence
Modeling the Anti-Symmetric Sector
A Minimal Model for the ao Component
Summary and Discussion
Full Text
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