Emergence of skewed non-Gaussian distributions of velocity increments in isotropic turbulence

W. Sosa-Correa, R. M. Pereira, A. M. S. Macedo, E. P. Raposo, D. S. P. Salazar, and G. L. Vasconcelos

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Dec 11, 2018
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Received Date: 29th November 18

Skewness and non-Gaussian behavior are key features of the distribution of short-scale velocity increments in isotropic turbulent flows [1,2]. Yet, the physical origin of the asymmetry and the form of the heavy tails remain elusive. Here we describe the emergence of such properties through an exactly solvable stochastic model with a hierarchy of multiple scales of energy transfer rates. By a statistical superposition of a local equilibrium distribution weighted by a background density, the increments distribution is given by a novel class of skewed heavy-tailed distributions, written as a generalization of the Meijer $G$-functions. Excellent agreement in the multiscale scenario is found with numerical data of systems with different sizes and Reynolds numbers. Remarkably, the single scale limit provides poor fits to the background density, highlighting the key role of the multiple scales. Our framework can be applied to describe the challenging emergence of skewed distributions in complex systems.

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