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The present work studied various models for predicting turbulence in the problem of injecting a fluid microjet into the boundary layer of a turbulent flow. For this purpose, the one-equation Spalart-Allmaras (SA), two-equation k-$\epsilon$…

Recent remarkable progress in computing power and numerical analysis is enabling us to fill a gap in the dynamical systems approach to turbulence. One of the significant advances in this respect has been the numerical discovery of simple…

Fluid Dynamics · Physics 2013-01-28 Genta Kawahara , Markus Uhlmann , Lennaert van Veen

We investigated turbulence in atomic Bose-Einstein condensates (BECs) using a minimally destructive, impurity injection technique analogous to particle image velocimetry in conventional fluids. Our approach transfers small regions of the…

Quantum Gases · Physics 2025-07-03 Mingshu Zhao , Junheng Tao , Ian Spielman

We present an analytical model for the time-developing turbulent boundary layer (TD-TBL) over a flat plate. The model provides explicit formulae for the temporal behavior of the wall-shear stress and both the temporal and spatial…

Chaotic Dynamics · Physics 2009-11-13 Victor S. L'vov , Anna Pomyalov , Antonino Ferrante , Said Elghobashi

This paper extends our recent theoretical work concerning the feasibility of stable and accurate computation of turbulence using a large eddy simulation [Ida and Taniguchi, Phys. Rev. E 68, 036705 (2003)]. In our previous paper, it was…

Fluid Dynamics · Physics 2007-05-23 Masato Ida , Nobuyuki Taniguchi

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

A probabilistic machine learning model is introduced to augment the $k-\omega\ SST$ turbulence model in order to improve the modelling of separated flows and the generalisability of learnt corrections. Increasingly, machine learning methods…

Computational Engineering, Finance, and Science · Computer Science 2023-01-24 Joel Ho , Nick Pepper , Tim Dodwell

Generative artificial intelligence has shown remarkable success in synthesizing data that mimic complex real-world systems, but its potential role in the discovery of mathematically meaningful structures in physical models remains…

Fluid Dynamics · Physics 2026-02-27 Jeremy P Parker , Tobias M Schneider

To characterize fluctuations in a turbulent flow, one usually studies different moments of velocity increments and dissipation rate, $\overline{(v(x+r)-v(x))^{n}}\propto r^{\zeta_{n}}$ and $\overline{{\cal E}^{n}}\propto Re^{d_{n}}$,…

Fluid Dynamics · Physics 2019-05-29 Victor Yakhot , Diego A. Donzis

An a priori reduced order method based on the proper generalised decomposition (PGD) is proposed to compute parametric solutions involving turbulent incompressible flows of interest in an industrial context, using OpenFOAM. The PGD…

Computational Physics · Physics 2021-11-16 Vasileios Tsiolakis , Matteo Giacomini , Ruben Sevilla , Carsten Othmer , Antonio Huerta

The rigorous justification of the hydrodynamic limits of kinetic equations in bounded domains has been actively investigated in recent years. In spite of the progress for the diffuse-reflection boundary case, the more challenging in-flow…

Analysis of PDEs · Mathematics 2023-04-04 Zhimeng Ouyang , Lei Wu

Turbulence is most commonly associated with high Reynolds number flow, however the framework of turbulent dynamics has been conceptually extended to many other fields, such as magnetohydrodynamic turbulence, elastic wave turbulence in…

Soft Condensed Matter · Physics 2026-03-05 Wilhelm Sunde Lie , Ingve Simonsen , Paul Gunnar Dommersnes

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

In this paper, we first propose a filter-based continuous Ensemble Eddy Viscosity (EEV) model for stochastic turbulent flow problems. We then propose a generic algorithm for a family of fully discrete, grad-div regularized, efficient…

Numerical Analysis · Mathematics 2025-08-15 Brandiece N. Berry , Md Mahmudul Islam , Muhammad Mohebujjaman , Neethu Suma Raveendran

We address the dynamical and statistical description of stably stratified turbulent boundary layers with the important example of the atmospheric boundary layer with a stable temperature stratification in mind. Traditional approaches to…

Chaotic Dynamics · Physics 2009-02-18 Victor S. L'vov , Itamar Procaccia , Oleksii Rudenko

A local artificial neural network (LANN) framework is developed for turbulence modeling. The Reynolds-averaged Navier-Stokes (RANS) unclosed terms are reconstructed by artificial neural network (ANN) based on the local coordinate system…

Fluid Dynamics · Physics 2021-09-08 Chenyue Xie , Xiangming Xiong , Jianchun Wang

Neither molecular kinetics nor continuum fluid dynamics alone is adequate to describe multiscale gas flows across different regimes. Bridging these regimes within a single self-consistent framework has long been a central challenge in fluid…

Fluid Dynamics · Physics 2026-02-24 Zhaoli Guo , Kun Xu , Yajun Zhu

Several new families of nonlinear three-dimensional travelling wave solutions to the Navier-Stokes equation, also known as exact coherent states, are computed for Newtonian plane Poiseuille flow. The symmetries and streak/vortex structures…

Fluid Dynamics · Physics 2015-10-28 Jae Sung Park , Michael D. Graham

The description of electron-electron interactions in transport problems is both analytically and numerically difficult. Here we show that a much simpler description of electron transport in the presence of interactions can be achieved in…

Strongly Correlated Electrons · Physics 2009-11-11 Roberto D'Agosta , Massimiliano Di Ventra

The Sagdeev-Zaslavski (SZ) equation for wave turbulence is analytically derived, both in terms of generating function and of multi-point pdf, for weakly interacting waves with initial random phases. When also initial amplitudes are random,…

Statistical Mechanics · Physics 2017-09-12 Sergio Chibbaro , Giovanni Dematteis , Christophe Josserand , Lamberto Rondoni
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