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Related papers: Fully developed turbulence and the multifractal co…

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Turbulent flows are notoriously difficult to describe and understand based on first principles. One reason is that turbulence contains highly intermittent bursts of vorticity and strain-rate with highly non-Gaussian statistics.…

Fluid Dynamics · Physics 2007-05-23 C. Meneveau , Y. Li

We study a correspondence between the multifractal model of turbulence and the Navier-Stokes equations in $d$ spatial dimensions by comparing their respective dissipation length scales. In Kolmogorov's 1941 theory the key parameter $h$,…

Fluid Dynamics · Physics 2022-02-16 B. Dubrulle , J. D. Gibbon

Understanding turbulence is the key to our comprehension of many natural and technological flow processes. At the heart of this phenomenon lies its intricate multi-scale nature, describing the coupling between different-sized eddies in…

Disentangling the evolution of a coherent mean-flow and turbulent fluctuations, interacting through the non-linearity of the Navier-Stokes equations, is a central issue in fluid mechanics. It affects a wide range of flows, such as planetary…

Fluid Dynamics · Physics 2018-05-23 Anna Frishman , Corentin Herbert

We suggested a one-fluid model of a turbulent dilute suspension which accounts for the ``two-way'' fluid-particle interactions by $k$-dependent effective density of suspension and additional damping term in the Navier-Stokes equation. We…

Chaotic Dynamics · Physics 2007-05-23 Victor S. L'vov , Anna Pomyalov

We study the Lagrangian trajectories of statistically isotropic, homogeneous, and stationary divergence free spatiotemporal random vector fields. We design this advecting Eulerian velocity field such that it gets asymptotically rough and…

Fluid Dynamics · Physics 2020-07-08 Jason Reneuve , Laurent Chevillard

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

Modeling turbulent flows by a random Fourier decomposition is a classical procedure in order to use simplified models of turbulence in heat transport and other applications. We carefully investigate the Fourier time series of…

Mathematical Physics · Physics 2026-05-14 Paolo Cifani , Franco Flandoli , Andrea Zanoni

In this study, we propose a computational method for solving the turbulence problem of incompressible viscous Newtonian fluids based on the extended Navier-Stokes (N-S) equations. With some phenomenological observations and H. J. Kreuer's…

Fluid Dynamics · Physics 2023-06-21 Shanwen Tan , Zhengui Li , Wangxu Li

The large deformations and break up of circular 2D liquid patches in a high Reynolds number (Re=1000) gas flow are investigated numerically. The 2D, plane flow Navier--Stokes equations are directly solved with explicit tracking of the…

chao-dyn · Physics 2009-10-28 S. Zaleski , Jie Li , S. Succi

The decay of turbulent and laminar oblique bands in the lower transitional range of plane Couette flow is studied by means of direct numerical simulations of the Navier--Stokes equations. We consider systems that are extended enough for…

Fluid Dynamics · Physics 2015-05-28 Paul Manneville

The probability density function of velocity fluctuations of {\em glanulence} observed by Radjai and Roux in their two-dimensional simulation of a slow granular flow under homogeneous quasistatic shearing is studied by the multifractal…

Soft Condensed Matter · Physics 2007-05-23 N. Arimitsu , T. Arimitsu

The existence and dynamical role of particular unstable Navier-Stokes solutions (exact coherent structures) is revealed in laboratory studies of weak turbulence in a thin, electromagnetically-driven fluid layer. We find that the dynamics…

Chaotic Dynamics · Physics 2018-08-01 Balachandra Suri , Jeffrey Tithof , Roman O. Grigoriev , Michael F. Schatz

The characterization of intermittency in turbulence has its roots in the K62 theory, and if no proper definition is to be found in the literature, statistical properties of intermittency were studied and models were developed in attempt to…

Fluid Dynamics · Physics 2021-07-14 Roxane Letournel , Ludovic Goudenège , Rémi Zamansky , Aymeric Vié , Marc Massot

We discuss averaged turbulence modeling of multi-scales of length for an incompressible Newtonian fluid, with the help of the maximum information principle. We suppose that there exists a function basis to decompose the turbulent…

Fluid Dynamics · Physics 2010-09-10 L. Tao , M. Ramakrishna

Numerical and analytical studies of decaying, two-dimensional (2D) Navier-Stokes (NS) turbulence at high Reynolds numbers are reported. The effort is to determine computable distinctions between two different formulations of maximum entropy…

Fluid Dynamics · Physics 2009-11-07 Z. Yin , D. C. Montgomery , H. J. H. Clercx

We here exploit a rigorous mathematical theory of vorticity dynamics for Navier-Stokes solutions in terms of stochastic Lagrangian flows and their stochastic Cauchy invariants, that are conserved on average backward in time. This theory…

Fluid Dynamics · Physics 2023-07-19 Gregory L. Eyink , Akshat Gupta , Tamer Zaki

We revisit the issue of Lagrangian irreversibility in the context of recent results [Xu, et al., PNAS, 111, 7558 (2014)] on flight-crash events in turbulent flows and show how extreme events in the Eulerian dissipation statistics are…

Fluid Dynamics · Physics 2020-04-22 Jason R. Picardo , Akshay Bhatnagar , Samriddhi Sankar Ray

We explore one-point and two-point statistics of the Navier-Stokes-alpha-beta regularization model at moderate Reynolds number in homogeneous isotropic turbulence. The results are compared to the limit cases of the Navier-Stokes-alpha model…

Fluid Dynamics · Physics 2014-08-14 Denis F. Hinz , Tae-Yeon Kim , Eliot Fried

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