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We investigate the statistics of turbulence in emulsions of two-immiscible fluids of same density. We compute for the first time velocity increments between points conditioned to be located in the same phase or in different phases and…

In this paper, we study the statistical evolution of the large-scale structure (LSS), focusing on the joint probability distribution function (PDF) of the coarse-grained cosmic field and its role in constructing effective dynamics. As the…

Cosmology and Nongalactic Astrophysics · Physics 2021-10-20 Xin Wang

In this visualisation the instantaneous local velocity is expressed in terms of four components to capture the development of and interactions between coherent structures in turbulent flows. It is then possible to isolate the terms linked…

Fluid Dynamics · Physics 2009-10-13 Trinh Khanh Tuoc

The understanding of the dynamics of the velocity gradients in turbulent flows is critical to understanding various non-linear turbulent processes. The pressure-Hessian and the viscous-Laplacian govern the evolution of the…

Machine Learning · Computer Science 2019-11-20 Nishant Parashar , Sawan S. Sinha , Balaji Srinivasan

The influence of turbulent effects on a fluid flow through a (pseudo) porous media is studied by numerically solving the set of Reynolds-averaged Navier-Stokes equations with the $\kappa$-$\epsilon$ model for turbulence. The spatial domains…

Statistical Mechanics · Physics 2009-11-07 H. H. M. Vasconcelos , U. M. S. Costa , M. P. Almeida

The evolution of probability distribution functions (PDFs) of continuous density, velocity and velocity derivatives ( deformation tensor) fields in the theory of cosmological gravitational instability are considered. We show that in the…

Astrophysics · Physics 2007-05-23 Lev Kofman

We propose an alternative interpretation of Markovian transport models based on the well-mixedness condition, in terms of the properties of a random velocity field with second order structure functions scaling linearly in the space time…

Chaotic Dynamics · Physics 2009-11-10 Piero Olla , Paolo Paradisi

An open problem arising in the statistical description of turbulence is related to the \textit{theoretical prediction based on first principles} of the so-called multi-point velocity probability density functions (PDFs) characterizing a…

Fluid Dynamics · Physics 2010-03-10 C. Asci , M. Tessarotto

Subcritical transition of an inhomogeneous plasma where turbulences with different characteristic space-time scales coexist is analyzed with methods of statistical physics of turbulences. We derived the development equations of the…

Plasma Physics · Physics 2007-05-23 Mitsuhiro Kawasaki , Sanae-I. Itoh , Kimitaka Itoh

A volume-filtered Euler-Lagrange large eddy simulation methodology is used to predict the physics of turbulent liquid-solid slurry flow through a horizontal pipe. A dynamic Smagorinsky model based on Lagrangian averaging is employed to…

Fluid Dynamics · Physics 2014-12-03 Sunil K. Arolla , Olivier Desjardins

In Lagrangian turbulence one is faced with the puzzle that 2D Navier-Stokes flows are nearly as intermittent as in three dimensions although no intermittency is present in the inverse cascade in 2D Eulerian turbulence. In addition, an…

Fluid Dynamics · Physics 2007-05-23 Rudolf Friedrich , Rainer Grauer , Holger Homann , Oliver Kamps

We study the probability distribution function (PDF) of the mass density in simulations of supersonic turbulence with properties appropriate for molecular clouds. For this study we use Athena, a new higher-order Godunov code. We find there…

Astrophysics · Physics 2008-09-23 M. Nicole Lemaster , James M. Stone

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes…

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…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 F. Böttcher , St. Barth , J. Peinke

Synthesizing fully developed three-dimensional turbulent velocity fields remains a long-standing problem in fluid mechanics and an open challenge for generative modeling. The difficulty arises from the coexistence of extreme dimensionality,…

Fluid Dynamics · Physics 2026-03-16 Tianyi Li , Michele Buzzicotti , Fabio Bonaccorso , Luca Biferale

In this work, we aimed to replicate and extend the results presented in the DiffFluid paper[1]. The DiffFluid model showed that diffusion models combined with Transformers are capable of predicting fluid dynamics. It uses a denoising…

Fluid Dynamics · Physics 2025-07-14 Yannick Gachnang , Vismay Churiwala

The statistics of power fluctuations are studied in simulations of two-dimensional turbulence in both inverse (energy) and direct (enstrophy) cascade regimes from both Lagrangian and Eulerian perspectives. The probability density function…

Statistical Mechanics · Physics 2008-03-01 M. M. Bandi , C. Connaughton

Turbulent flows consist of a wide range of interacting scales. Since the scale range increases as some power of the flow Reynolds number, a faithful simulation of the entire scale range is prohibitively expensive at high Reynolds numbers.…

Fluid Dynamics · Physics 2023-07-24 Dhawal Buaria , Katepalli R. Sreenivasan

We present the first prediction of the probability distribution function (PDF) for self-organization of shear flows modeled by a nonlinear diffusion equation with a stochastic forcing. A novel non-perturbative method based on a coherent…

Fluid Dynamics · Physics 2009-04-26 Eun-jin Kim , Han-Li Liu , Johan Anderson

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…

Statistical Mechanics · Physics 2015-03-19 Toshihico Arimitsu , Naoko Arimitsu , Kohei Takechi , Yukio Kaneda , Takashi Ishihara
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