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The majority of practical flows, particularly those flows in applications of importance to transport, distribution and climate, are turbulent and as a result experience complex three-dimensional motion with increased drag compared with the…

流体动力学 · 物理学 2015-03-17 B. J. McKeon , A. S. Sharma , I. Jacobi

In operational weather models, the effects of turbulence in the atmospheric boundary layer (ABL) on the resolved flow are modeled using turbulence parameterizations. These parameterizations typically use a predetermined set of model…

流体动力学 · 物理学 2025-05-27 E. Y. Shin , M. F. Howland

A model for the pseudo-turbulent Reynolds stress tensor in compressible flows through monodisperse particle clouds is developed based on data from particle resolved numerical simulations. This model extends previous models for the…

流体动力学 · 物理学 2025-05-09 Andreas Nygård Osnes , Magnus Vartdal

We present an overview of recent works on the statistical description of turbulent flows in terms of probability density functions (PDFs) in the framework of the Lundgren-Monin-Novikov (LMN) hierarchy. Within this framework, evolution…

流体动力学 · 物理学 2013-03-19 R. Friedrich , A. Daitche , O. Kamps , J. Lülff , M. Voßkuhle , M. Wilczek

We analyze the data stemming from a forced incompressible hydrodynamic simulation on a grid of 2048^3 regularly spaced points, with a Taylor Reynolds number of Re~1300. The forcing is given by the Taylor-Green flow, which shares…

流体动力学 · 物理学 2009-11-13 P. D. Mininni , A. Alexakis , A. Pouquet

Neural networks offer highly expressive turbulence closures, yet their complexity obscures the physical mechanisms they aim to model, and their computational cost can limit their tractability. To address these limitations, we introduce a…

流体动力学 · 物理学 2026-04-29 Samantha Friess , Aviral Prakash , John A. Evans

Direct numerical simulation (DNS) of turbulent flows is computationally expensive and cannot be applied to flows with large Reynolds numbers. Large eddy simulation (LES) is an alternative that is computationally less demanding, but is…

流体动力学 · 物理学 2021-09-09 Shengyu Chen , Shervin Sammak , Peyman Givi , Joseph P. Yurko1 , Xiaowei Jia

We study freely decaying quantum turbulence by performing high resolution numerical simulations of the Gross-Pitaevskii equation (GPE) in the Taylor-Green geometry. We use resolutions ranging from $1024^3$ to $4096^3$ grid points. The…

In our recent works we proposed a theory of turbulence in inertial gas flow via the mean field effect of an intermolecular potential. We found that, in inertial flow, turbulence indeed spontaneously develops from a laminar initial…

流体动力学 · 物理学 2022-12-14 Rafail V. Abramov

We investigate vortex breakdown (VB) and its dominant topologies in turbulent, non-reacting flows within a canonical swirl combustor using large-eddy simulations (LES). A baseline configuration and operating conditions are first used to…

流体动力学 · 物理学 2026-02-24 Nitesh Kumar Sahu , Anupam Dewan , Mayank Kumar

Providing evidence of finite-time singularities of the incompressible Euler equations in three space dimensions is still an unsolved problem. Likewise, the zeroth law of turbulence has not been proven to date by numerical experiments. We…

流体动力学 · 物理学 2020-07-06 Niklas Fehn , Martin Kronbichler , Peter Munch , Wolfgang A Wall

So-called engineering or analytical wind farm flow solvers typically build upon two submodels: one for the velocity deficit and one for the wake-added turbulence intensity. While velocity deficit modelling has received considerable…

流体动力学 · 物理学 2026-05-01 Frédéric Blondel , Erwan Jézéquel , Helen Schottenhamml , Majid Bastankhah

We perform direct numerical simulations (DNS) of a turbulent channel flow over porous walls. In the fluid region the flow is governed by the incompressible Navier--Stokes (NS) equations, while in the porous layers the Volume-Averaged…

流体动力学 · 物理学 2023-07-19 Marco E. Rosti , Luca Cortelezzi , 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…

计算工程、金融与科学 · 计算机科学 2023-01-24 Joel Ho , Nick Pepper , Tim Dodwell

Large Eddy Simulation (LES) of turbulent non-Newtonian flows involves two additional closures, namely the Non-Newtonian SubGrid-Scale (NNSGS) stress tensor and filtered viscosity. Here, dynamic closures are proposed for NNSGS, eliminating…

流体动力学 · 物理学 2025-11-14 E. Amani , A. Ahmadpour , M. J. Aghajari

The dynamics of the Reynolds stress tensor for turbulent flows is described with an evolution equation coupling both geometric effects and turbulent source terms. The effects of the mean flow geometry are shown up when the source terms are…

经典物理 · 物理学 2017-08-23 Sergey L. Gavrilyuk , Henri Gouin

We present a description and validation of a finite volume solver aimed at solving the problems of microscale urban flows where vegetation is present. The solver is based on the five equation system of Reynolds-averaged Navier-Stokes…

流体动力学 · 物理学 2016-09-13 Viktor Šíp , Luděk Beneš

Recent experiments have reported a novel transition to elasto-inertial turbulence in the Taylor--Couette flow of a dilute polymer solution. Unlike previously reported transitions, this newly discovered scenario, dubbed vortex merging and…

流体动力学 · 物理学 2022-08-24 Jose M. Lopez

Even though compressible plasma turbulence is encountered in many astrophysical phenomena, its effect is often not well understood. Furthermore, direct numerical simulations are typically not able to reach the extreme parameters of these…

流体动力学 · 物理学 2016-07-27 P. Grete , D. G. Vlaykov , W. Schmidt , D. R. G. Schleicher

Fluidic transport in inverted T-shaped cavities with the flow entering through the top and exiting from the two bottom outlets experiences an interesting phenomenon that causes particles having density lower than that of the fluid medium to…

流体动力学 · 物理学 2022-11-15 Sneham Das , Saikat Basu