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Related papers: Enstrophy dissipation in two-dimensional turbulenc…

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We consider two-dimensional flows above topography, revisiting the selective decay (or minimum-enstrophy) hypothesis of Bretherton and Haidvogel. We derive a 'condensed branch' of solutions to the variational problem where a domain-scale…

Fluid Dynamics · Physics 2024-06-11 Basile Gallet

We study the temporal dissipation of variance and relative entropy for ergodic Markov Chains in continuous time, and compute explicitly the corresponding dissipation rates. These are identified, as is well known, in the case of the variance…

Probability · Mathematics 2022-05-19 Ioannis Karatzas , Jan Maas , Walter Schachermayer

Two dimensional turbulence has a remarkable tendency to self-organize into large, coherent structures, forming a mean flow. The purpose of this paper is to elucidate how these structures are sustained, and what determines them and the…

Fluid Dynamics · Physics 2018-02-05 Anna Frishman

Decay of honeycomb-generated turbulence in a duct with a static transverse magnetic field is studied via direct numerical simulations. The simulations follow the revealing experimental study of Sukoriansky et al. (1986), in particular the…

Fluid Dynamics · Physics 2019-05-01 Oleg Zikanov , Dmitry Krasnov , Thomas Boeck , Semion Sukoriansky

In the quest to understand the basic universal features of compressible convection, one would like to disentangle genuine consequences of compression from spatial variations of transport properties. In the present work, we consider a very…

We derive equations for the mean entropy and the mean internal energy in the low-Mach-number temperature stratified turbulence (i.e., for turbulent convection or stably stratified turbulence), and show that turbulent flux of entropy is…

Fluid Dynamics · Physics 2015-12-16 Igor Rogachevskii , Nathan Kleeorin

In previous papers I have argued that the \emph{fusion rules hypothesis}, which was originally introduced by L'vov and Procaccia in the context of the problem of three-dimensional turbulence, can be used to gain a deeper insight in…

Chaotic Dynamics · Physics 2015-05-13 Eleftherios Gkioulekas

Harmonic oscillations of the walls of a turbulent plane channel flow are studied by direct numerical simulations to improve our understanding of the physical mechanism for skin-friction drag reduction. The simulations are carried out at…

Fluid Dynamics · Physics 2017-04-26 Pierre Ricco , Claudio Ottonelli , Yosuke Hasegawa , Maurizio Quadrio

Wall turbulence has a sublayer where the mean wall-normal flux of the streamwise momentum is constant. Via the law of the wall, this mean flux is related to the wall-normal profile of the mean streamwise velocity. However, the momentum flux…

Fluid Dynamics · Physics 2023-07-10 H. Mouri , J. Ito

The aim of this paper is to understand the tendency to organization of the turbulence in two-dimensional ideal fluids. We show that nonlinear processes as inverse cascade of the energy and vorticity concentration are essentially determined…

Fluid Dynamics · Physics 2016-01-20 M. Vlad , F. Spineanu

We derive relativistic hydrodynamic equations with a dynamical spin degree of freedom on the basis of an entropy-current analysis. The first and second laws of local thermodynamics constrain possible structures of the constitutive relations…

High Energy Physics - Theory · Physics 2019-07-03 Koichi Hattori , Masaru Hongo , Xu-Guang Huang , Mamoru Matsuo , Hidetoshi Taya

Enstrophy is an averaged measure of fluid vorticity. This quantity is particularly important in {\em rotating} geophysical flows. We investigate the dynamical evolution of enstrophy for large-scale quasi-geostrophic flows under random wind…

Analysis of PDEs · Mathematics 2020-05-29 D. Blömker , Jinqiao Duan , T. Wanner

Systems coupled to multiple thermodynamic reservoirs can exhibit nonequilibrium dynamics, breaking detailed balance to generate currents. To power these currents, the entropy of the reservoirs increases. The rate of entropy production, or…

Statistical Mechanics · Physics 2019-04-16 Junang Li , Jordan M. Horowitz , Todd R. Gingrich , Nikta Fakhri

For the steady-state direct cascade of two-dimensional Navier-Stokes turbulence, we derive analytically the probability of strong vorticity fluctuations. The probability density function (pdf) of the vorticity coarse-grained over a scale in…

Chaotic Dynamics · Physics 2015-05-20 Gregory Falkovich , Vladimir Lebedev , Mikhail Stepanov

Freely decaying two-dimensional Navier--Stokes turbulence is studied. The conservation of vorticity by advective nonlinearities renders a class of Casimirs that decays under viscous effects. A rigorous constraint on the palinstrophy…

Chaotic Dynamics · Physics 2009-11-11 Chuong V. Tran

We show that in the linear response approximation only entropy provides coupling between thermal and electric phenomena. The dissipationless quantum currents -- magnetization, superconducting, persistent and topological edge currents -- do…

General Physics · Physics 2022-03-24 Andrei Sergeev , Michael Reizer

We introduce a quantum stochastic dynamics for heat conduction. A multi-level subsystem is coupled to reservoirs at different temperatures. Energy quanta are detected in the reservoirs allowing the study of steady state fluctuations of the…

Statistical Mechanics · Physics 2007-05-23 Wojciech De Roeck , Christian Maes

Many theoretical expressions of dissipation along non-equilibrium processes have been proposed. However, they have not been fully verified by experiments. Especially for systems strongly interacting with environments the connection between…

Statistical Mechanics · Physics 2019-12-03 Ketan Goyal , Xian He , Ryoichi Kawai

Entropy and the fluctuation-dissipation theorem are at the heart of statistical mechanics near equilibrium. Driving a system beyond the linear response regime leads to (i) the breakdown of the fluctuation-dissipation theorem and (ii) a…

Statistical Mechanics · Physics 2010-09-10 Thomas Speck

The entropy of network ensembles characterizes the amount of information encoded in the network structure, and can be used to quantify network complexity, and the relevance of given structural properties observed in real network datasets…

Disordered Systems and Neural Networks · Physics 2014-06-18 Kartik Anand , Dimitri Krioukov , Ginestra Bianconi