English
Related papers

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

200 papers

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

We discuss a theoretical framework to define an optimal sub-grid closure for shell models of turbulence. The closure is based on the ansatz that consecutive shell multipliers are short-range correlated, following the third hypothesis of…

Fluid Dynamics · Physics 2017-04-26 Luca Biferale , Alexei A. Mailybaev , Giorgio Parisi

Turbulent flow remains a challenging subject, despite extensive efforts to find analytical descriptions. Modeling small scales of motion is crucial for saving time and resources in numerical simulations, particularly in industrial…

Fluid Dynamics · Physics 2025-08-13 Julia Domingues Lemos , Fabio Pereira dos Santos

We explore the utility of the recently proposed alpha equations in providing a subgrid model for fluid turbulence. Our principal results are comparisons of direct numerical simulations of fluid turbulence using several values of the…

chao-dyn · Physics 2009-10-31 Shiyi Chen , Darryl D. Holm , Len G. Margolin , Raoyang Zhang

Shell models have found wide application in the study of hydrodynamic turbulence because they are easily solved numerically even at very large Reynolds numbers. Although bereft of spatial variation, they accurately reproduce the main…

Chaotic Dynamics · Physics 2021-08-11 Dario Vincenzi , John D. Gibbon

When simulating multiscale systems, where some fields cannot be fully prescribed despite their effects on the simulation's accuracy, closure models are needed. This phenomenon is observed in turbulent fluid dynamics, where Large Eddy…

Fluid Dynamics · Physics 2025-12-01 Eduardo Vital , Jean-Marc Gratien , Yassine Ayoun , Thibault Faney , Julien Bohbot

Turbulence modeling remains a longstanding challenge in fluid dynamics. Recent advances in data-driven methods have led to a surge of novel approaches aimed at addressing this problem. This work builds upon our recent work [Phys. Rev.…

Fluid Dynamics · Physics 2026-02-24 André Freitas , Kiwon Um , Mathieu Desbrun , Michele Buzzicotti , Luca Biferale

Turbulent flows exhibit large intermittent fluctuations from inertial to dissipative scales, characterized by multifractal statistics and breaking the statistical self-similarity. It has recently been proposed that the Navier-Stokes…

Fluid Dynamics · Physics 2025-07-08 B. Magacho , S. Thalabard , M. Buzzicotti , F. Bonaccorso , L Biferale , A. A. Mailybaev

Following the exact decomposition in eigenstates of helicity for the Navier-Stokes equations in Fourier space [F. Waleffe, Phys. Fluids A 4, 350 (1992)] we introduce a modified version of helical shell models for turbulence with non-local…

Fluid Dynamics · Physics 2015-11-04 Massimo De Pietro , Luca Biferale , Alexei A. Mailybaev

A simplified Lagrangean closure for the Navier-Stokes equation is used to study the production of intermittency in the inertial range of three dimensional turbulence. This is done using localized wavepackets following the fluid rather than…

chao-dyn · Physics 2009-10-22 Piero Olla

Deterministic closures for coarse-grained turbulence models help reproduce mean statistics, but often fail to capture the finite-time growth of uncertainty. Using the framework of shell models as a quantitative multi-scale testbed, we…

We study shell models that conserve the analogues of energy and enstrophy, hence designed to mimic fluid turbulence in 2D. The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous…

chao-dyn · Physics 2009-10-22 E. Aurell , G. Boffetta , A. Crisanti , P. Frick , G. Paladin , A. Vulpiani

Complex spatial and temporal structures are inherent characteristics of turbulent fluid flows and comprehending them poses a major challenge. This comprehesion necessitates an understanding of the space of turbulent fluid flow…

Fluid Dynamics · Physics 2024-07-16 Tim Whittaker , Romuald A. Janik , Yaron Oz

Generalizability of machine-learning (ML) based turbulence closures to accurately predict unseen practical flows remains an important challenge. At the Reynolds-averaged Navier-Stokes (RANS) level, NN-based turbulence closure modeling is…

Fluid Dynamics · Physics 2021-12-15 Salar Taghizadeh , Freddie Witherden , Yassin Hassan , Sharath Girimaji

Cellular suspensions such as dense bacterial flows exhibit a turbulence-like phase under certain conditions. We study this phenomenon of "active turbulence" statistically by using numerical tools. Following Wensink et al. [Proc. Natl. Acad.…

Fluid Dynamics · Physics 2018-02-15 Martin James , Michael Wilczek

A data-driven framework for formulation of closures of the Reynolds-Average Navier--Stokes (RANS) equations is presented. In recent years, the scientific community has turned to machine learning techniques to distill a wealth of highly…

Fluid Dynamics · Physics 2020-09-02 S. Beetham , J. Capecelatro

Reduced wavenumber models of turbulence, shell models, show cascade processes and anomalous scaling of correlators which might be analogous to what is observed in Navier-Stokes (N-S) turbulence. The scaling properties of the shell models…

chao-dyn · Physics 2007-05-23 P. D. Ditlevsen

It is known that scale invariance is broken in the developed hydrodynamic turbulence due to intermittency, substantiating complexity of turbulent flows. Here we challenge the concept of broken scale invariance by establishing a hidden…

Fluid Dynamics · Physics 2021-01-20 Alexei A. Mailybaev

Fully-developed incompressible Navier-Stokes turbulence in three dimensions is a dissipative dynamical system that exhibits strong departure from absolute equilibrium. Nevertheless, several kinds of representation by Tsallis equilibria have…

Chaotic Dynamics · Physics 2009-11-10 Toshiyuki Gotoh , Robert H. Kraichnan

In turbulence modeling, we are concerned with finding closure models that represent the effect of the subgrid scales on the resolved scales. Recent approaches gravitate towards machine learning techniques to construct such models. However,…

Numerical Analysis · Mathematics 2024-03-18 Toby van Gastelen , Wouter Edeling , Benjamin Sanderse
‹ Prev 1 2 3 10 Next ›