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Related papers: Geometric Intermittency in Turbulence

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Collective movements of bacteria exhibit a remarkable pattern of turbulence-like vortices, in which the Richardson cascade plays an important role. In this work, we examine the energy and enstrophy cascades and their associated lognormal…

Fluid Dynamics · Physics 2024-10-03 Yongxiang Huang

We apply a simple method to provide explicit expressions for different scaling exponents in intermittent fully developed turbulence, that before were only given through a Legendre transform. This includes predictability exponents for…

Fluid Dynamics · Physics 2009-11-11 Francois G Schmitt

Many fluid-dynamical systems met in nature are quasi-two-dimensional: they are constrained to evolve in approximately two dimensions with little or no variation along the third direction. This has a drastic effect in the flow evolution…

Fluid Dynamics · Physics 2024-11-14 Alexandros Alexakis

The way the increment statistics of turbulent velocity fluctuations scale with the increment size is a centerpiece of turbulence theories. We report data on decaying turbulence in the Max Planck Variable Density Turbulence Tunnel (VDTT),…

Fluid Dynamics · Physics 2022-03-07 Christian Küchler , Eberhard Bodenschatz , Gregory P. Bewley

We consider general infinite-dimensional dynamical systems with the Galilean and spatiotemporal scaling symmetry groups. Introducing the equivalence relation with respect to temporal scalings and Galilean transformations, we define a…

Mathematical Physics · Physics 2022-06-29 Alexei A. Mailybaev

We study the statistical properties of stationary, isotropic and homogeneous turbulence in two-dimensional (2D) flows, focusing on the direct cascade, that is on wave-numbers large compared to the integral scale, where both energy and…

Statistical Mechanics · Physics 2024-08-29 Malo Tarpin , Léonie Canet , Carlo Pagani , Nicolás Wschebor

Turbulence problem is often considered as "the last unsolved problem of classical physics". It is due to strong interaction between velocity and/or velocity gradient fluctuations, a high Reynolds number flow is a fascinating mixture of…

Fluid Dynamics · Physics 2017-08-25 Victor Yakhot , Diego A. Donzis

Intermittency is one of central obstacles for understanding small-scale dynamics in the fully developed hydrodynamic turbulence. The modern approach is largely based on the multifractal theory of Parisi and Frisch which is, however,…

Fluid Dynamics · Physics 2023-05-12 Alexei A. Mailybaev

The stability of flows in layers of finite thickness $H$ is examined against small scale three dimensional (3D) perturbations and large scale two-dimensional (2D) perturbations. The former provide an indication of a forward transfer of…

Fluid Dynamics · Physics 2018-06-04 Alexandros Alexakis

Turbulence exhibits significant velocity fluctuations even if the scale is much larger than the scale of the energy supply. Since any spatial correlation is negligible, these large-scale fluctuations have many degrees of freedom and are…

Fluid Dynamics · Physics 2015-05-20 H. Mouri , A. Hori , Y. Kawashima , K. Hashimoto

Turbulent flow evolution and energy cascades are significantly different in two-dimensional (2D) and three-dimensional (3D) flows. Studies have investigated these differences in obstacle-free turbulent flows, but solid boundaries have an…

Fluid Dynamics · Physics 2020-08-21 Bernat Font , Gabriel D. Weymouth , Vinh-Tan Nguyen , Owen R. Tutty

We study the statistical properties of orientation and rotation dynamics of elliptical tracer particles in two-dimensional, homogeneous and isotropic turbulence by direct numerical simulations. We consider both the cases in which the…

Fluid Dynamics · Physics 2014-03-19 Anupam Gupta , Dario Vincenzi , Rahul Pandit

The statistical properties of turbulent flows are fundamentally different from those of systems at equilibrium due to the presence of an energy flux from the scales of injection to those where energy is dissipated by the viscous forces: a…

Statistical Mechanics · Physics 2024-01-17 Niccolò Cocciaglia , Massimo Cencini , Angelo Vulpiani

Polymeric turbulence, flows of fluids with dilute polymer additives at high Reynolds numbers, exhibits striking deviations from the Kolmogorovean behaviour of Newtonian turbulence. Recent experiments as well as simulations have uncovered a…

Fluid Dynamics · Physics 2025-07-30 Alessandro Chiarini , Rahul K. Singh , Marco E. Rosti

In this paper we discuss the dynamical features of intermittent fluctuations in homogeneous shear flow turbulence. In this flow the energy cascade is strongly modified by the production of turbulent kinetic energy related to the presence of…

Chaotic Dynamics · Physics 2007-05-23 P. Gualtieri , C. M Casciola , R. Benzi , G. Amati , R. Piva

The separating and reattaching turbulent flow past a rectangular cylinder is studied to describe how small and large scales contribute to the sustaining mechanism of the velocity fluctuations. The work is based on the Anisotropic…

Fluid Dynamics · Physics 2022-08-24 Alessandro Chiarini , Davide Gatti , Andrea Cimarelli , Maurizio Quadrio

We report on the observation of surface gravity wave turbulence at scales larger than the forcing ones in a large basin. In addition to the downscale transfer usually reported in gravity wave turbulence, an upscale transfer is observed,…

We investigate through Direct Numerical Simulations (DNS) the statistical properties of turbulent flows in the inertial subrange for non-Newtonian power-law fluids. The structural invariance found for the vortex size distribution is…

Fluid Dynamics · Physics 2019-06-12 H. J. Seybold , H. A. Carmona , H. J. Herrmann , J. S. Andrade

We use high resolution direct numerical simulations to study the anisotropic contents of a turbulent, statistically homogeneous flow with random transitions among multiple energy containing states. We decompose the velocity correlation…

Fluid Dynamics · Physics 2017-07-05 Kartik P. Iyer , Fabio Bonaccorso , Luca Biferale , Federico Toschi

Deep learning provides a versatile suite of methods for extracting structured information from complex datasets, enabling deeper understanding of underlying fluid dynamic phenomena. The field of turbulence modeling, in particular, benefits…

Machine Learning · Computer Science 2025-07-31 Anuraj Maurya