Abstract
We discuss the application of stochastic intermittency fields to describe and analyse the statistical properties of time series of the generalised turbulence intensity in an anisotropic and inhomogeneous turbulent flow and provide a parsimonious description of the one-, two-, and three-point statistics. In particular, we show that the three-point correlations can be predicted from observed two-point statistics. Our analysis is motivated by observed stylised features of the energy dissipation in homogeneous and isotropic situations where these statistical properties are well represented within the framework of stochastic intermittency fields. We find a close resemblance and conclude that stochastic intermittency fields may be relevant in more general situations.
Highlights
We propose that stochastic intermittency fields and the statistical properties implied by them may be of relevance in a wider range of applications than previously anticipated
Motivated by statistical properties observed for the energy dissipation in homogeneous and isotropic turbulent flows, the statistical properties of the generalised turbulence intensity in a non-homogeneous and non-isotropic flow situation are analysed in relation to characteristic statistics implied by stochastic intermittency fields
We observe a close resemblance with respect to the type of marginal distributions and the statistical properties of two-point and three-point correlators
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations Cascade processes and their representation in terms of stochastic intermittency fields constitute a fundamental stochastic framework that captures strongly intermittent fluctuations and long range correlations with scaling properties [1,2,3,4,5,6,7]. We analyse the generalised turbulence intensity in a von Kármán Experiment with focus on a particular set of such statistical properties and their realisation within the framework of stochastic intermittency fields, namely self-scaling of correlators [9] and the representation of three-point statistics in terms of two-point statistics [2,10].
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