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Turbulence models, such as the Smagorinsky model herein, are used to represent the energy lost from resolved to under-resolved scales due to the energy cascade (i.e. non-linearity). Analytic estimates of the energy dissipation rates of a…

Numerical Analysis · Mathematics 2019-04-24 Ali Pakzad

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…

Fluid Dynamics · Physics 2021-06-23 K. R. Sreenivasan , V. Yakhot

Linearly stable shear flows first transition to turbulence in the form of localised patches. At low Reynolds numbers, these turbulent patches tend to suddenly decay, following a memoryless process typical of rare events. How far in advance…

Fluid Dynamics · Physics 2025-07-10 Daniel Morón , Alberto Vela-Martín , Marc Avila

We present results from two 1536^3 direct numerical simulations of rotating turbulence where both energy and helicity are injected into the flow by an external forcing. The dual cascade of energy and helicity towards smaller scales observed…

Fluid Dynamics · Physics 2015-05-14 P. D. Mininni , A. Pouquet

Using direct numerical simulation we study the behavior of the maximal Lyapunov exponent in thin-layer turbulence, where one dimension of the system is constrained geometrically. Such systems are known to exhibit transitions from fully…

Fluid Dynamics · Physics 2021-06-02 Daniel Clark , Andres Armua , Calum Freeman , Daniel J. Brener , Arjun Berera

A new velocity scale is derived that yields a Reynolds number independent profile for the streamwise turbulent fluctuations in the near-wall region of wall bounded flows for $y^+<25$. The scaling demonstrates the important role played by…

Fluid Dynamics · Physics 2024-02-06 Marcus Hultmark , Alexander J. Smits

We study the chaotic properties of a turbulent conducting fluid using direct numerical simulation in the Eulerian frame. The maximal Lyapunov exponent is measured for simulations with varying Reynolds number and magnetic Prandtl number. We…

Fluid Dynamics · Physics 2019-05-22 Richard Ho , Arjun Berera , Daniel Clark

Decaying three-dimensional (3D) turbulence is studied via direct numerical simulations (DNS) for an isotropic non-rotating flow and for rotating flows with and without helicity. We analyze the cases of moderate Rossby number and large…

Fluid Dynamics · Physics 2015-05-14 T. Teitelbaum , P. D. Mininni

Developed turbulent motion of fluid still lacks an analytical description despite more than a century of active research. Nowadays phenomenological ideas are widely used in practical applications, such as small-scale closures for numerical…

Fluid Dynamics · Physics 2023-08-04 Julia Domingues Lemos , Alexei A. Mailybaev

Direct numerical simulation is used to investigate the decay exponent of isotropic homogeneous turbulence over a range of Reynolds numbers sufficient to display both high and low Re number decay behavior. The initial turbulence is generated…

Fluid Dynamics · Physics 2010-07-29 J. Blair Perot

We perform direct numerical simulation of the incompressible Navier-Stokes equation with forcing at different spatial dimensions and measure turbulent and chaotic properties. Lyapunov exponents, $\lambda$, decrease with dimension, and…

The predictability problem for systems with different characteristic time scales is investigated. It is shown that even in simple chaotic dynamical systems, the leading Lyapunov exponent is not sufficient to estimate the predictability…

chao-dyn · Physics 2009-10-31 G. Boffetta , P. Giuliani , G. Paladin , A. Vulpiani

A solvable turbulent model is used to predict both the structure of the boundary layer and the scaling laws in thermal convection. The transport of heat depends on the interplay between the thermal, viscous and integral scales of…

Fluid Dynamics · Physics 2015-05-28 B. Dubrulle

We use high resolution numerical simulations over several hundred of turnover times to study the influence of small scale dissipation onto vortex statistics in 2D decaying turbulence. A self-similar scaling regime is detected when the…

Statistical Mechanics · Physics 2009-10-31 Jean-Philippe Laval , Pierre-Henri Chavanis , Bérengère Dubrulle , Clément Sire

Shell models provide a simplified mathematical framework that captures essential features of incompressible fluid turbulence, such as the energy cascade and scaling of the fluid observables. We perform a precision analysis of the direct and…

Fluid Dynamics · Physics 2024-09-19 James Creswell , Viatcheslav Mukhanov , Yaron Oz

Lyapunov exponents measure the average exponential growth rate of typical linear perturbations in a chaotic system, and the inverse of the largest exponent is a measure of the time horizon over which the evolution of the system can be…

Fluid Dynamics · Physics 2017-11-22 Prakash Mohan , Nicholas Fitzsimmons , Robert D. Moser

We report a high-resolution numerical study of two-dimensional (2D) miscible Rayleigh-Taylor (RT) incompressible turbulence with the Boussinesq approximation. An ensemble of 100 independent realizations were performed at small Atwood number…

Fluid Dynamics · Physics 2015-06-16 Quan Zhou

We study sign changes and scaling laws in the Cartesian components of the velocity and vorticity of rotating turbulence, in the helicity, and in the components of vertically-averaged fields. Data for the analysis is provided by…

Fluid Dynamics · Physics 2013-06-05 E. Horne , P. D. Mininni

By tracking the divergence of two initially close trajectories in phase space in an Eulerian approach to forced turbulence, the relation between the maximal Lyapunov exponent $\lambda$, and the Reynolds number $Re$ is measured using direct…

Fluid Dynamics · Physics 2018-01-31 A. Berera , R. D. J. G. Ho

Helicity transfer in a shell model of turbulence is investigated. We show that a Reynolds-independent helicity flux is present in the model when the large scale forcing breaks inversion symmetry. The equivalent in Shell Models of the ``2/15…

chao-dyn · Physics 2009-10-30 L. Biferale , D. Pierotti , F. Toschi