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Related papers: A Numerical Proof of Shell Model Turbulence Closur…

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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

The connection between anomalous scaling of structure functions (intermittency) and numerical methods for turbulence simulations is discussed. It is argued that the computational work for direct numerical simulations (DNS) of fully…

Chaotic Dynamics · Physics 2009-11-11 Victor Yakhot , Katepalli R. Sreenivasan

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

There exists continuous demand of improved turbulence models for the closure of Reynolds Averaged Navier-Stokes (RANS) simulations. Machine Learning (ML) offers effective tools for establishing advanced empirical Reynolds stress closures on…

Fluid Dynamics · Physics 2021-04-01 Muyuan Liu , Yiren Yang , Hao Chen

A recent Letter by Oberlack et al. [Phys. Rev. Lett. 128, 024502 (2022)] claims to have derived new symmetry-induced solutions of the non-modelled statistical Navier-Stokes equations of turbulent channel flow. A high accuracy match to DNS…

Fluid Dynamics · Physics 2023-02-13 Michael Frewer , George Khujadze

A closure model is presented for large-eddy simulation (LES) based on the three-dimensional variational data assimilation algorithm. The approach aims at reconstructing high-fidelity kinetic energy spectra in coarse numerical simulations by…

Fluid Dynamics · Physics 2024-07-02 Sagy Ephrati , Arnout Franken , Erwin Luesink , Paolo Cifani , Bernard Geurts

Fluid turbulence is characterized by strong coupling across a broad range of scales. Furthermore, besides the usual local cascades, such coupling may extend to interactions that are non-local in scale-space. As such the computational…

The majority of practical flows, particularly those flows in applications of importance to transport, distribution and climate, are turbulent and as a result experience complex three-dimensional motion with increased drag compared with the…

Fluid Dynamics · Physics 2015-03-17 B. J. McKeon , A. S. Sharma , I. Jacobi

We formulate and implement the Euler equations with SGS dynamics and provide numerical tests of an SGS turbulence energy model that predicts the turbulent pressure of unresolved velocity fluctuations and the rate of dissipation for highly…

Astrophysics of Galaxies · Physics 2015-05-20 W. Schmidt , C. Federrath

We report numerical investigations of wave turbulence in a vibrating plate. The possibility to implement advanced measurement techniques and long time numerical simulations makes this system extremely valuable for wave turbulence studies.…

Soft Condensed Matter · Physics 2017-10-25 Nicolas Mordant , Benjamin Miquel

We discuss a stochastic closure for the equation of motion satisfied by multi-scale correlation functions in the framework of shell models of turbulence. We give a systematic procedure to calculate the anomalous scaling exponents of…

Chaotic Dynamics · Physics 2007-05-23 Roberto Benzi , Luca Biferale , Mauro Sbragaglia , Federico Toschi

Ultrametric structure of the energy cascade process in a dynamical model of turbulence is studied. The tree model we use can be viewed as an approximated one-dimensional truncation of the wavelets resolved Navier-Stokes dynamics. Varying…

chao-dyn · Physics 2009-10-30 R. Benzi , L. Biferale , E. Trovatore

In this investigation, a data-driven turbulence closure framework is introduced and deployed for the sub-grid modelling of Kraichnan turbulence. The novelty of the proposed method lies in the fact that snapshots from high-fidelity numerical…

Fluid Dynamics · Physics 2018-11-14 Romit Maulik , Omer San , Adil Rasheed , Prakash Vedula

Deep learning is increasingly becoming a promising pathway to improving the accuracy of sub-grid scale (SGS) turbulence closure models for large eddy simulations (LES). We leverage the concept of differentiable turbulence, whereby an…

In a recent paper it was proposed that for some nonlinear shell models of turbulence one can construct a linear advection model for an auxiliary field such that the scaling exponents of all the structure functions of the linear and…

Chaotic Dynamics · Physics 2009-11-11 Roberto Benzi , Boris Levant , Itamar Procaccia , Edriss S. Titi

We consider cascade models of turbulence which are obtained by restricting the Navier-Stokes equation to local interactions. By combining the results of the method of extended self-similarity and a novel subgrid model, we investigate the…

chao-dyn · Physics 2008-02-03 C. Uhlig , J. Eggers

We present a methodology to determine the best turbulence closure for an eddy-permitting ocean model through measurement of the error-landscape of the closure's subgrid spectral transfers and flux. We apply this method to 6 different…

Fluid Dynamics · Physics 2015-06-05 Jonathan Pietarila Graham , Todd Ringler

We propose a simple stochastic model of cascading transport in wave number space to clarify the origin of intermittent behavior of fully-developed fluid turbulence. In spite of lack of nonlinearity and viscosity the model gives non-Gaussian…

chao-dyn · Physics 2008-02-03 Hideki Takayasu , Y-h. Taguchi , Tomoo Katsuyama

Despite the nonlinear nature of wall turbulence, there is evidence that the energy-injection mechanisms sustaining wall turbulence can be ascribed to linear processes. The different scenarios stem from linear stability theory and comprise…

Accurate subgrid-scale closures are essential for weather/climate models, where predicting extreme events is critical. Traditional closures have structural errors, e.g., producing excessive diffusion that dampens extremes. Artificial…