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相关论文: Small scales and anisotropy in low $Rm$ magnetohyd…

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Steady Low $R_m$ MHD turbulence is investigated here through estimates of upper bounds for attractor dimension. A flow between two parallel walls with an imposed perpendicular magnetic field is considered. The flow is defined by its maximum…

流体动力学 · 物理学 2020-06-09 Alban Pothérat , Thierry Alboussière

The aim of the present work is to derive rigorous estimates for turbulent MHD flow quantities such as the size and anisotropy of the dissipative scales, as well as the transition between 2D and 3D state. To this end, we calculate an upper…

流体动力学 · 物理学 2020-06-11 Alban Pothérat , Thierry Alboussière

We investigate aspects of low-magnetic-Reynolds-number flow between two parallel, perfectly insulating walls, in the presence of an imposed magnetic field parallel to the bounding walls. We find a functional basis to describe the flow, well…

流体动力学 · 物理学 2015-05-29 Robert Low , Alban Potherat

We accomplish two major tasks. First, we show that the turbulent motion at large scales obeys Gaussian statistics in the interval 0 < Rlambda < 8.8, where Rlambda is the microscale Reynolds number, and that the Gaussian flow breaks down to…

流体动力学 · 物理学 2021-06-23 K. R. Sreenivasan , V. Yakhot

This study is concerned with how the attractor dimension of the two-dimensional Navier--Stokes equations depends on characteristic length scales, including the system integral length scale, the forcing length scale, and the dissipation…

混沌动力学 · 物理学 2007-05-23 Chuong V. Tran , Theodore G. Shepherd , Han-Ru Cho

The problem of anomalous scaling in magnetohydrodynamics turbulence is considered within the framework of the kinematic approximation, in the presence of a large-scale background magnetic field. The velocity field is Gaussian,…

混沌动力学 · 物理学 2009-10-31 N. V. Antonov , A. Lanotte , A. Mazzino

We investigate using direct numerical simulations with grids up to 1536^3 points, the rate at which small scales develop in a decaying three-dimensional MHD flow both for deterministic and random initial conditions. Parallel current and…

流体动力学 · 物理学 2007-05-23 P. D. Mininni , A. Pouquet , D. C. Montgomery

We derive upper bounds for the number of degrees of freedom of two-dimensional Navier--Stokes turbulence freely decaying from a smooth initial vorticity field $\omega(x,y,0)=\omega_0$. This number, denoted by $N$, is defined as the minimum…

流体动力学 · 物理学 2015-05-13 Chuong V. Tran , Luke Blackbourn

We present Direct Numerical Simulations of decaying Magnetohydrodynamic (MHD) turbulence at low magnetic Reynolds number. The domain considered is bounded by periodic boundary conditions in the two directions perpendicular to the magnetic…

流体动力学 · 物理学 2015-03-19 Kacper Kornet , Alban Potherat

When magnetohydrodynamic turbulence evolves in the presence of a large-scale mean magnetic field, an anisotropy develops relative to that preferred direction. The well-known tendency is to develop stronger gradients perpendicular to the…

等离子体物理 · 物理学 2020-07-15 Rohit Chhiber , William H. Matthaeus , Sean Oughton , Tulasi N. Parashar

This study seeks to elucidate the linear transient growth mechanisms in a uniform duct with square cross-section applicable to flows of electrically conducting fluids under the influence of an external magnetic field. A particular focus is…

流体动力学 · 物理学 2019-01-30 Oliver G. W. Cassells , Tony Vo , Alban Pothérat , Gregory J. Sheard

Magnetohydrodynamic (MHD) turbulence in the majority of natural systems, including the interstellar medium, the solar corona, and the solar wind, has Reynolds numbers far exceeding the Reynolds numbers achievable in numerical experiments.…

太阳与恒星天体物理 · 物理学 2015-06-22 J. C. Perez , J. Mason , S. Boldyrev , F. Cattaneo

The three-dimensional Navier-Stokes-$\alpha$ model for fast rotating geophysical fluids is considered. The Navier-Stokes-$\alpha$ model is a nonlinear dispersive regularization of the exact Navier-Stokes equations obtained by Lagrangian…

偏微分方程分析 · 数学 2019-03-05 Bong-Sik Kim

We present a new analysis of the anisotropic spectral energy distribution in incompressible magnetohydrodynamic (MHD) turbulence permeated by a strong mean magnetic field. The turbulent flow is generated by high-resolution pseudo-spectral…

等离子体物理 · 物理学 2015-05-19 Roland Grappin , Wolf-Christian Müller

We present numerical simulations and explore scalings and anisotropy of compressible magnetohydrodynamic (MHD) turbulence. Our study covers both gas pressure dominated (high beta) and magnetically dominated (low beta) plasmas at different…

天体物理学 · 物理学 2011-05-05 Jungyeon Cho , A. Lazarian

In this work we derive a lower bounds for the Hausdorff and fractal dimensions of the global attractor of the Sabra shell model of turbulence in different regimes of parameters. We show that for a particular choice of the forcing and for…

流体动力学 · 物理学 2009-11-13 Peter Constantin , Boris Levant , Edriss S. Titi

This article establishes estimates on the dimension of the global attractor of the two-dimensional rotating Navier-Stokes equation for viscous, incompressible fluids on the $\beta$-plane. Previous results in this setting by M.A.H.…

偏微分方程分析 · 数学 2025-03-07 Aseel Farhat , Anuj Kumar , Vincent R. Martinez

A method is proposed for computing coefficients in the Kazantsev equation of small-scale dynamo for the full spectrum of hydromagnetic turbulence comprising the inertial range together with the range of viscous dissipation. The dynamo…

流体动力学 · 物理学 2026-04-03 Leonid Kitchatinov

This manuscript has been accepted for publication in Physical Review Fluids, see https://journals.aps.org/prfluids/accepted/d5074S28J6b11905012b7cb06505e8f2149dd5f20. This work investigates the mechanisms that underlie transitions to…

流体动力学 · 物理学 2020-12-24 Christopher J. Camobreco , Alban Pothérat , Gregory J. Sheard

Deep autoencoder neural networks can generate highly accurate, low-order representations of turbulence. We design a new family of autoencoders which are a combination of a 'dense-block' encoder-decoder structure (Page et al, J. Fluid Mech.…

流体动力学 · 物理学 2025-10-22 Andrew Cleary , Jacob Page
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