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Turbulence is a fundamental flow phenomenon, typically anisotropic at large scales and approximately isotropic at small scales. The classical Kolmogorov scaling laws (2/3, -5/3 and 4/5) have been well-established for turbulence without…

Fluid Dynamics · Physics 2025-04-08 Yong-Ying Zeng , Zi-Ju Liao , Jun-Yi Li , Wei-Dong Su

In computational fluid dynamics simulations of industrial flows, models based on the Reynolds-averaged Navier--Stokes (RANS) equations are expected to play an important role in decades to come. However, model uncertainties are still a major…

Fluid Dynamics · Physics 2018-10-01 Heng Xiao , Paola Cinnella

We provide a first-principles approach to turbulence by employing the electrodynamics of continuous media at the viscous limit to recover the Navier-Stokes equations. We treat oscillators with two orthogonal angular momenta as a spin…

General Physics · Physics 2026-01-30 Chris Scott

Solving the Reynolds-averaged Navier-Stokes equations (RANS) closed with an eddy viscosity computed through a turbulence model is still the leading approach for Computational Fluid Dynamics simulations. Unfortunately, universal models with…

Fluid Dynamics · Physics 2025-09-18 Marco Castelletti , Maurizio Quadrio

Turbulence is a complex system exhibiting both universal statistical features and prominent coherent structures. We model turbulence using coherent vortices distributed within a multi-scale statistical framework, termed `woven turbulence'.…

Fluid Dynamics · Physics 2025-12-04 Zishuo Han , Weiyu Shen , Yue Yang

An open question of whether phenomenological fluid equations to be used for direct numerical simulation of turbulence are warranted on `first principles' is addressed, and the problem is posed using Klimontovich microscopic density to…

chao-dyn · Physics 2007-05-23 Shunichi Tsuge

Turbulence is one of the most prototypical phenomena of systems driven out of equilibrium. While turbulence has been studied mainly with classical fluids like water, considerable attention is now drawn to quantum turbulence (QT), observed…

Quantum Gases · Physics 2016-09-07 Masahiro Takahashi , Michikazu Kobayashi , Kazumasa A. Takeuchi

We develop first-principles theory of relativistic fluid turbulence at high Reynolds and P\'eclet numbers. We follow an exact approach pioneered by Onsager, which we explain as a non-perturbative application of the principle of…

Fluid Dynamics · Physics 2018-02-21 Gregory L. Eyink , Theodore D. Drivas

Turbulence -- ubiquitous in nature and engineering alike [1-5] -- is traditionally viewed as an intrinsically inertial phenomenon, emerging only when the Reynolds number (Re), which quantifies the ratio of inertial to dissipative forces…

Fluid Dynamics · Physics 2025-11-11 Ziyue Yu , Xinyu Si , Lei Fang

It has been recently demonstrated, [3], that according to the principle of release of constraints, absence of shear stresses in the Euler equations must be compensated by additional degrees of freedom, and that led to a Reynolds-type…

General Physics · Physics 2013-02-12 Michail Zak

In-depth analyses of existing direct numerical simulations (DNS) data from various sources supported a logical and important classification of generic turbulent boundary layers (TBL), namely Type-A, -B and -C TBL, based on distribution…

Fluid Dynamics · Physics 2019-04-19 Duo Wang , Heng Li , Ting Yu , Bochao Cao , Hongyi Xu

Numerical models based on Reynolds-Averaged Navier-Stokes (RANS) equations are widely used in engineering turbulence modeling. However, the RANS predictions have large model-form uncertainties for many complex flows. Quantification of these…

Computational Physics · Physics 2017-01-25 Jian-Xun Wang , Rui Sun , Heng Xiao

A stochastic Euler equation is proposed, describing the motion of a particle density, forced by the random action of virtual photons in vacuum. After time averaging, the Euler equation is reduced to the Reynolds equation, well studied in…

Quantum Physics · Physics 2019-05-09 Roumen Tsekov , Eyal Heifetz , Eliahu Cohen

With the rising of modern data science, data--driven turbulence modeling with the aid of machine learning algorithms is becoming a new promising field. Many approaches are able to achieve better Reynolds stress prediction, with much lower…

Fluid Dynamics · Physics 2020-06-19 Xianwen Guo , Zhenhua Xia , Heng Xiao , Jinlong Wu , Shiyi Chen

Turbulence in fluids is an ubiquitous phenomenon, characterized by spontaneous transition of a smooth, laminar flow to rapidly changing, chaotic dynamics. In 1883, Reynolds experimentally demonstrated that, in an initially laminar flow of…

Fluid Dynamics · Physics 2022-05-03 Rafail V. Abramov

Modeling of wall-bounded turbulent flows is still an open problem in classical physics, with only modest progress made in the last few decades beyond the so-called `log law', which describes only the intermediate region in wall-bounded…

Fluid Dynamics · Physics 2018-08-31 Fangying Song , George Em Karniadakis

It has previously been shown that by increasing the Reynolds number across a channel by spatially varying the viscosity does not cause an immediate change in the size of turbulent structures and a delay is in fact observed in both wall…

Fluid Dynamics · Physics 2021-06-11 Victor Coppo Leite , Elia Merzari

Following the idea that dissipation in turbulence at high Reynolds number is by events singular in space-time and described by solutions of the inviscid Euler equations, we draw the conclusion that in such flows scaling laws should depend…

Fluid Dynamics · Physics 2020-01-01 Yves Pomeau , Martine Le Berre

Despite the fundamentally different dissipation mechanisms, many laws and phenomena of classical turbulence equivalently manifest in quantum turbulence. The Reynolds law of dynamical similarity states that two objects of same geometry…

The recent study by Klingenberg, Oberlack & Pluemacher (2020) proposes a new strategy for modeling turbulence in general. A proof-of-concept is presented therein for the particular flow configuration of a spatially evolving turbulent planar…

Fluid Dynamics · Physics 2022-06-06 George Khujadze , Michael Frewer