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相关论文: Theory for the single-point velocity statistics of…

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The purpose of the present paper is to derive a partial differential equation (PDE) for the single-time single-point probability density function (PDF) of the velocity field of a turbulent flow. The PDF PDE is a highly non-linear…

数学物理 · 物理学 2021-07-08 Jiawei Li , Zhongmin Qian , Mingrui Zhou

The probability density function (PDF) of velocity fluctuations is studied experimentally for grid turbulence in a systematical manner. At small distances from the grid, where the turbulence is still developing, the PDF is sub-Gaussian. At…

流体动力学 · 物理学 2009-11-07 H. Mouri , M. Takaoka , A. Hori , Y. Kawashima

We investigate the single-point probability density function of the velocity in three-dimensional stationary and decaying homogeneous isotropic turbulence. To this end we apply the statistical framework of the Lundgren-Monin-Novikov…

流体动力学 · 物理学 2011-07-04 Michael Wilczek , Anton Daitche , Rudolf Friedrich

We study local power fluctuations in numerical simulations of stationary, homogeneous, isotropic turbulence in two and three dimensions with Gaussian forcing. Due to the near-Gaussianity of the one-point velocity distribution, the…

统计力学 · 物理学 2009-11-13 M. M. Bandi , Sergei G. Chumakov , Colm Connaughton

Turbulence is essential for understanding the structure and dynamics of molecular clouds and star-forming regions. There is a need for adequate tools to describe and characterize the properties of turbulent flows. One-point probability…

天体物理学 · 物理学 2008-11-26 Ralf S. Klessen

We show that the tails of the single-point velocity probability distribution function (PDF) are generally non-Gaussian in developed turbulence. By using instanton formalism for the Navier-Stokes equation, we establish the relation between…

chao-dyn · 物理学 2009-10-30 Gregory Falkovich , Vladimir Lebedev

The probability density functions (PDFs) for energy dissipation rates, created from time-series data of grid turbulence in a wind tunnel, are analyzed in a high precision by the theoretical formulae for PDFs within multifractal PDF theory…

流体动力学 · 物理学 2015-06-03 Toshihico Arimitsu , Naoko Arimitsu , Hideaki Mouri

An analytical formula for the probability density function (PDF) of the velocity fluctuation in fully-developed turbulence is derived, non-perturbatively, by assuming that its underlying statistics is the one based on the generalized…

统计力学 · 物理学 2015-06-24 Toshihico Arimitsu , Naoko Arimitsu

In probability density function (PDF) methods a transport equation is solved numerically to compute the time and space dependent probability distribution of several flow variables in a turbulent flow. The joint PDF of the velocity…

流体动力学 · 物理学 2010-06-04 J. Bakosi , P. Franzese , Z. Boybeyi

We elaborate the statistical field theory of Turbulence suggested in the previous paper \cite{M20a}. We clarify and simplify the basic Energy pumping equation of that theory and study mathematical properties of singular field configuration…

高能物理 - 理论 · 物理学 2020-10-13 Alexander Migdal

We study density fluctuations in supersonic turbulence using both theoretical methods and numerical simulations. A theoretical formulation is developed for the probability distribution function (PDF) of the density at steady state,…

星系天体物理 · 物理学 2019-09-04 Liubin Pan , Paolo Padoan , Åke Nordlund

The phenomenology of velocity statistics in turbulent flows, up to now, relates to different models dealing with either signed or unsigned longitudinal velocity increments, with either inertial or dissipative fluctuations. In this paper, we…

统计力学 · 物理学 2007-05-23 L. Chevillard , B. Castaing , E. Leveque , A. Arneodo

We study the one-point probability distribution functions (PDFs) of the peculiar velocity and the density fluctuation in a cosmological fluid. Within the perturbative approach to the structure formation scenario, the effect of ``pressure''…

天体物理学 · 物理学 2009-11-11 Takayuki Tatekawa

The vorticity random field of turbulent flow is singled out as the main dynamical variable for the description of turbulence, and the evolution equation of the probability density function (PDF) of the vorticity field has been obtained.…

流体动力学 · 物理学 2022-02-23 Jiawei Li , Zhongmin Qian , Mingrui Zhou

We consider the tails of probability density function (PDF) for the velocity that satisfies Burgers equation driven by a Gaussian large-scale force. The saddle-point approximation is employed in the path integral so that the calculation of…

chao-dyn · 物理学 2015-06-24 E. Balkovsky , G. Falkovich , I. Kolokolov , V. Lebedev

The probability distribution functions of the circulation of velocity in three-dimensional decaying isotropic turbulence are examined by the database of the numerical simulation based on the pseudospectral method. It is shown that the…

高能物理 - 理论 · 物理学 2009-10-22 Makoto Umeki

The statistical properties of the $E \times B$ flux in different types of plasma turbulence simulations are investigated using probability density distribution functions (PDF). The physics included in the models ranges from two dimensional…

等离子体物理 · 物理学 2009-11-10 Volker Naulin , Odd Erik Garcia , Anders Henry Nielsen , Jens Juul Rasmussen

Atmospheric wind speeds and their fluctuations at different locations (onshore and offshore) are examined. One of the most striking features is the marked intermittency of probability density functions (PDF) of velocity differences -- no…

适应与自组织系统 · 物理学 2007-05-23 F. Böttcher , St. Barth , J. Peinke

We introduce a method for calculating the probability density function (PDF) of a turbulent density field in three dimensions using only information contained in the projected two-dimensional column density field. We test the method by…

星系天体物理 · 物理学 2015-05-18 Christopher M. Brunt , Christoph Federrath , Daniel J. Price

The PDFs for energy dissipation rates created in a high resolution from $4096^3$ DNS for fully developed turbulence are analyzed in a high precision with the PDF derived within the formula of multifractal probability density function theory…

统计力学 · 物理学 2015-03-19 Toshihico Arimitsu , Naoko Arimitsu , Kohei Takechi , Yukio Kaneda , Takashi Ishihara
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