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A deep learning (DL) closure model for large-eddy simulation (LES) is developed and evaluated for incompressible flows around a rectangular cylinder at moderate Reynolds numbers. Near-wall flow simulation remains a central challenge in…

Fluid Dynamics · Physics 2023-07-19 Justin Sirignano , Jonathan F. MacArt

S3T (Stochastic Structural Stability Theory) employs a closure at second order to obtain the dynamics of the statistical mean turbulent state. When S3T is implemented as a coupled set of equations for the streamwise mean and perturbation…

Lagrangian properties obtained from a Particle Tracking Velocimetry experiment in a turbulent flow at intermediate Reynolds number are presented. Accurate sampling of particle trajectories is essential in order to obtain the Lagrangian…

Fluid Dynamics · Physics 2015-05-13 Jacob Berg , Soren Ott , Jakob Mann , Beat Luthi

Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics and plasma physics. Fluids are well described by the Navier-Stokes equations, but solving these equations at…

Fluid Dynamics · Physics 2022-04-27 Dmitrii Kochkov , Jamie A. Smith , Ayya Alieva , Qing Wang , Michael P. Brenner , Stephan Hoyer

This paper presents a recent advancement that transforms the problem of decaying turbulence in the Navier-Stokes equations in $3+1$ dimensions into a Number Theory challenge: finding the statistical limit of the Euler ensemble. We redefine…

Fluid Dynamics · Physics 2024-10-18 Alexander Migdal

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

At sufficiently high Reynolds numbers, shear-flow turbulence close to a wall acquires universal properties. When length and velocity are rescaled by appropriate characteristic scales of the turbulent flow and thereby measured in \emph{inner…

Fluid Dynamics · Physics 2020-03-18 Sajjad Azimi , Tobias M. Schneider

How predictable are turbulent flows? Here we use theoretical estimates and shell model simulations to argue that Eulerian spontaneous stochasticity, a manifestation of the non-uniqueness of the solutions to the Euler equation that is…

Fluid Dynamics · Physics 2024-02-20 Dmytro Bandak , Alexei Mailybaev , Gregory L. Eyink , Nigel Goldenfeld

We demonstrate finite-time blow-up in a simple, realistic shell model of the 3D Navier-Stokes equations, equipped with "smooth" (i.e., rapidly decaying in frequency) initial data and forcing. Previously studied models either exhibit a…

Analysis of PDEs · Mathematics 2026-05-14 Stan Palasek

Although effective non-reciprocal interactions have been investigated in a variety of fields, their consequences have not been explored in hydrodynamical turbulence. We initiate such an exploration by introducing non-reciprocal binary-fluid…

Fluid Dynamics · Physics 2026-02-26 Biswajit Maji , Nadia Bihari Padhan , Axel Voigt , Rahul Pandit

Direct numerical simulations of turbulent flow in a channel with one rigid and one viscoelastic wall are performed. An Eulerian-Eulerian model is adopted with a level-set approach to identify the fluid-compliant material interface. Focus is…

Fluid Dynamics · Physics 2021-11-03 Amir Esteghamatian , Joseph Katz , Tamer A. Zaki

We propose a new approach to the old-standing problem of the anomaly of the scaling exponents of nonlinear models of turbulence. We achieve this by constructing, for any given nonlinear model, a linear model of passive advection of an…

Chaotic Dynamics · Physics 2009-11-11 Luiza Angheluta , Roberto Benzi , Luca Biferale , Itamar Procaccia , Federico Toschi

With increasing computational demand, Neural-Network (NN) based models are being developed as pre-trained surrogates for different thermohydraulics phenomena. An area where this approach has shown promise is in developing higher-fidelity…

Fluid Dynamics · Physics 2024-12-13 Cody Grogan , Som Dutta , Mauricio Tano , Somayajulu L. N. Dhulipala , Izabela Gutowska

In this paper, we propose an approach for simulating wall-bounded incompressible turbulent flows by integrating the technology of random vortex method with the core principles of large-eddy simulations (LES). In particular, we employ the…

Fluid Dynamics · Physics 2025-11-11 Zihao Guo , Zhongmin Qian

A recent theoretical development in the understanding of the small-scale structure of Navier-Stokes turbulence has been the proposition that the scales $\eta_n(R)$ that separate inertial from viscous behavior of many-point correlation…

chao-dyn · Physics 2009-10-30 Adrienne L. Fairhall , Victor S. L'vov , Itamar Procaccia

This manuscript is a draft of work in progress, meant for network distribution only. It will be updated to a formal preprint when the numerical calculations will be accomplished. In this draft we develop a consistent closure procedure for…

chao-dyn · Physics 2016-08-31 Victor I. Belinicher , Victor S. L'vov , Itamar Procaccia

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

Very recently, a defect model which depicts the growth tendency of the near-wall peak of the streamwise turbulence intensity has been developed (Chen $\&$ Sreenivasan, J. Fluid Mech. (2021), vol.908, R3). Based on the finiteness of the…

Fluid Dynamics · Physics 2023-03-30 Cheng Cheng , Lin Fu

Turbulence modeling is a classical approach to address the multiscale nature of fluid turbulence. Instead of resolving all scales of motion, which is currently mathematically and numerically intractable, reduced models that capture the…

Fluid Dynamics · Physics 2018-12-10 Rui Fang , David Sondak , Pavlos Protopapas , Sauro Succi

Neural networks of simple structures are used to construct a turbulence model for large-eddy simulation (LES). Data obtained by direct numerical simulation (DNS) of homogeneous isotropic turbulence are used to train neural networks. It is…

Fluid Dynamics · Physics 2020-12-04 Satoshi Miyazaki , Yuji Hattori