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We explore the ability of anisotropic permeable substrates to reduce turbulent skin-friction, studying the influence that these substrates have on the overlying turbulence. For this, we perform DNSs of channel flows bounded by permeable…

流体动力学 · 物理学 2020-07-21 Garazi Gómez-de-Segura , Ricardo García-Mayoral

The variance and spectra of wall-normal velocities are investigated for direct numerical simulations of turbulent flow in a channel, pipe, and zero-pressure-gradient boundary layer across a decade of friction Reynolds numbers. Spectra along…

流体动力学 · 物理学 2026-04-22 Michael Heisel , Rahul Deshpande , Gabriel G. Katul

We study the laminar and turbulent channel flow over a viscous hyper-elastic wall and show that it is possible to sustain an unsteady chaotic turbulent-like flow at any Reynolds number by properly choosing the wall elastic modulus. We…

流体动力学 · 物理学 2020-08-05 Marco E Rosti , Luca Brandt

Non-equilibrium wall turbulence with mean-flow three-dimensionality is ubiquitous in geophysical and engineering flows. Under these conditions, turbulence may experience a counter-intuitive depletion of the turbulent stresses, which has…

流体动力学 · 物理学 2020-01-08 Adrián Lozano-Durán , Marco Giometto , George I. Park , Parviz Moin

A Direct Numerical Simulation (DNS) of the incompressible flow around a rectangular cylinder with chord-to-thickness ratio 5:1 (also known as the BARC benchmark) is presented. The work replicates the first DNS of this kind recently…

流体动力学 · 物理学 2021-05-04 Alessandro Chiarini , Maurizio Quadrio Politecnico di Milano

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…

流体动力学 · 物理学 2025-11-11 Ziyue Yu , Xinyu Si , Lei Fang

Homogeneous anisotropic turbulence simulations are used to determine off-diagonal components of the Reynolds stress tensor and its parameterization in terms of turbulent viscosity and Lambda-effect. The turbulence is forced in an…

天体物理学 · 物理学 2011-11-10 P. J. Käpylä , A. Brandenburg

The supernova-driven interstellar medium in star-forming galaxies has Reynolds numbers of the order of $10^{6}$ or even larger. We study, by means of adaptive mesh refinement hydro- and magnetohydrodynamical simulations that cover the full…

天体物理学 · 物理学 2007-05-23 M. A. de Avillez , D. Breitschwerdt

The turbulence kinetic energy dissipation rate $\epsilon$, from a turbulent combustion computation using either Reynolds-averaged Navier-Stokes (RANS) or large-eddy simulation (LES), is proposed for closure with a sub-grid non-premixed…

流体动力学 · 物理学 2026-04-01 William A. Sirignano , Wes Hellwig , Sylvain L. Walsh

We examine the role of anisotropic subgrid-scale (SGS) stress in wall-modeled large-eddy simulation (WMLES) of flow over a spanwise-uniform Gaussian-shaped bump, with emphasis on predicting flow separation. The simulations show that…

流体动力学 · 物理学 2026-04-22 Di Zhou , H. Jane Bae

The velocity gradient tensor can be decomposed into normal straining, pure shearing and rigid rotation tensors, each with distinct symmetry and normality properties. We partition the strength of turbulent velocity gradients based on the…

流体动力学 · 物理学 2026-01-14 Rahul Arun , Tim Colonius

The temperature fluctuations generated by viscous dissipation in an isotropic turbulent flow are studied using direct numerical simulation. It is shown that their scaling with Reynolds number is at odds with predictions from recent…

流体动力学 · 物理学 2015-09-30 Wouter Bos , Robert Chahine , Andrey Pushkarev

In particle-laden turbulent flows the turbulence in carrier fluid phase gets affected by the dispersed particle phase for volume fraction above $10^{-4}$ and hence reverse coupling or two-way coupling becomes relevant in that volume…

流体动力学 · 物理学 2022-09-14 Swagnik Ghosh , Partha Sarathi Goswami

We introduce a novel approach to derive compressibility corrections for Reynolds-averaged Navier-Stokes (RANS) models. Using this approach, we derive variable-property corrections for wall-bounded flows that take into account the distinct…

流体动力学 · 物理学 2025-09-17 Asif Manzoor Hasan , Alex Jose Elias , Florian Menter , Rene Pecnik

(abridged) Context: Turbulent diffusion of large-scale flows and magnetic fields play major roles in many astrophysical systems. Aims: Our goal is to compute turbulent viscosity and magnetic diffusivity, relevant for diffusing large-scale…

太阳与恒星天体物理 · 物理学 2020-04-29 Petri J. Käpylä , Matthias Rheinhardt , Axel Brandenburg , Maarit J. Käpylä

Two mechanisms are considered responsible for the turbulence modification due to suspended particles in a turbulent gas-particle suspension. Turbulence augmentation is due to the enhancement of fluctuations by wakes behind particles,…

流体动力学 · 物理学 2018-11-19 V. Kumaran , P Muramalla , A. Tyagi , P. S. Goswami

Pore-resolved direct numerical simulations of turbulent open channel flow are performed comparing the structure and dynamics of turbulence over impermeable rough and smooth walls to a porous sediment bed at permeability Reynolds number…

流体动力学 · 物理学 2022-05-02 Shashank K. Karra , Sourabh V. Apte , Xiaoliang He , Timothy D. Scheibe

Results from Direct Numerical Simulations of particle relative dispersion in three dimensional homogeneous and isotropic turbulence at Reynolds number $Re_\lambda \sim 300$ are presented. We study point-like passive tracers and heavy…

流体动力学 · 物理学 2015-02-19 L. Biferale , A. S. Lanotte , R. Scatamacchia , F. Toschi

Passive scalars in turbulent channel flows are investigated as canonical problem for heat and mass transfer in turbulent boundary-layer flows. The one-dimensional turbulence model is used to numerically investigate the Schmidt and Reynolds…

流体动力学 · 物理学 2020-11-11 Marten Klein , Heiko Schmidt

The turbulent diffusivity tensor is determined for linear shear flow turbulence using numerical simulations. For moderately strong shear, the diagonal components are found to increase quadratically with Peclet and Reynolds numbers below…

太阳与恒星天体物理 · 物理学 2014-11-20 Eniko J. M. Madarassy , Axel Brandenburg