English
Related papers

Related papers: Turbulence and Tsallis Statistics

200 papers

We present the first experimental tests of the recently derived fusion rules for Navier-Stokes (N-S) turbulence. The fusion rules address the asymptotic properties of many-point correlation functions as some of the coordinates coalesce, and…

In this paper, we train turbulence models based on convolutional neural networks. These learned turbulence models improve under-resolved low resolution solutions to the incompressible Navier-Stokes equations at simulation time. Our study…

Fluid Dynamics · Physics 2022-10-12 Björn List , Li-Wei Chen , Nils Thuerey

Turbulence is a paradigm for far-from-equilibrium systems without time reversal symmetry. To capture the nonequilibrium irreversible nature of turbulence and investigate its implications, we develop a potential landscape and flux field…

Fluid Dynamics · Physics 2018-01-09 Wei Wu , Feng Zhang , Jin Wang

In this study the q-statistics of Tsallis theory is testified in various complex physical systems. Especially the Tsallis q-triplet is estimated for space plasmas atmospheric dynamics and seismogenesis as well as for the brain and cardiac…

Disentangling the evolution of a coherent mean-flow and turbulent fluctuations, interacting through the non-linearity of the Navier-Stokes equations, is a central issue in fluid mechanics. It affects a wide range of flows, such as planetary…

Fluid Dynamics · Physics 2018-05-23 Anna Frishman , Corentin Herbert

A model to explain the statistics of the velocity gradients in the dissipation range of a turbulent flow is presented. The experimentally observed non-gaussian statistics is theoretically predicted by means of a thermodynamical analogy…

Statistical Mechanics · Physics 2007-05-23 Jacopo Bellazzini

It is shown that the Truncated Euler Equations, i.e. a finite set of ordinary differential equations for the amplitude of the large-scale modes, can correctly describe the complex transitional dynamics that occur within the turbulent regime…

Chaotic Dynamics · Physics 2016-12-07 Vishwanath Shukla , Stephan Fauve , Marc Brachet

We solve the problem of spatial distribution of inertial particles that sediment in Navier-Stokes turbulence with small ratio $Fr$ of acceleration of fluid particles to acceleration of gravity $g$. The particles are driven by linear drag…

Fluid Dynamics · Physics 2014-10-31 Itzhak Fouxon , Yongnam Park , Roei Harduf , Changhoon Lee

We study the mechanism of energy injection from the mean flow to the fluctuating velocity necessary to maintain wall turbulence. This process is believed to be correctly represented by the linearized Navier--Stokes equations, and three…

Fluid Dynamics · Physics 2019-02-15 Adrián Lozano-Durán , Michael Karp , Navid. C. Constantinou

The randomly driven Navier-Stokes equation without pressure in d-dimensional space is considered as a model of strong turbulence in a compressible fluid. We derive a closed equation for the velocity-gradient probability density function. We…

High Energy Physics - Theory · Physics 2009-10-31 S. Boldyrev

A unique form of turbulent-transport equations is derived based on first principles.The role of nonequilibrium statistical mechanics employed to describe the phenomenology is that it enables to single out the unique form consistent with…

chao-dyn · Physics 2007-05-23 Shunichi Tsuge

Randomness is one of the most important characteristics of turbulence, but its origin remains an open question. By means of a ``thought experiment'' via several clean numerical experiments based on the Navier-Stokes equations for…

Fluid Dynamics · Physics 2025-07-29 Shijun Liao , Shijie Qin

The Reynolds number dependence of the statistics of energy dissipation is investigated in a shell model of fully developed turbulence. The results are in agreement with a model which accounts for fluctuations of the dissipative scale with…

chao-dyn · Physics 2009-10-31 G. Boffetta , A. Celani , D. Roagna

We study two-dimensional (2D) binary-fluid turbulence by carrying out an extensive direct numerical simulation (DNS) of the forced, statistically steady turbulence in the coupled Cahn-Hilliard and Navier-Stokes equations. In the absence of…

Fluid Dynamics · Physics 2017-04-06 Prasad Perlekar , Nairita Pal , Rahul Pandit

The incompressible Navier-Stokes equations currently represent the primary model for describing stratified turbulent fluid flows at low Mach number. The validity of the incompressible assumption, however, has so far only been rigorously…

Fluid Dynamics · Physics 2007-11-20 Remi Tailleux

The incompressible Navier-Stokes equations are considered. We find that there exist infinite non-trivial solutions of static Euler equations. Moreover there exist random solutions of static Euler equations. Provided Reynolds number is large…

Analysis of PDEs · Mathematics 2024-07-24 Yongqian Han

We discuss the phenomenology of the split energy cascade in a three-dimensional thin fluid layer by mean of high resolution numerical simulations of the Navier-Stokes equations. We observe the presence of both an inverse energy cascade at…

Fluid Dynamics · Physics 2017-08-11 Stefano Musacchio , Guido Boffetta

We present an analysis of the Navier-Stokes equations based on a spatial filtering technique to elucidate the multi-scale nature of fully developed turbulence. In particular, the advection of a band-pass-filtered small-scale contribution by…

Fluid Dynamics · Physics 2023-07-24 Theodore D. Drivas , Perry L. Johnson , Cristian C. Lalescu , Michael Wilczek

Hydrodynamic helicity signatures the parity symmetry breaking, chirality, of the flow. Statistical hydrodynamics thus respect chirality, as symmetry breaking and restoration are key to their fundamentals, such as the spectral transfer…

Fluid Dynamics · Physics 2014-08-01 Jian-Zhou Zhu

The transitional and well-developed regimes of turbulent shear flows exhibit a variety of remarkable scaling laws that are only now beginning to be systematically studied and understood. In the first part of this article, we summarize…

Fluid Dynamics · Physics 2017-01-04 Nigel Goldenfeld , Hong-Yan Shih