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A new approach to turbulence simulation, based on a combination of large-eddy simulation (LES) for the whole flow and an array of non-space-filling quasi-direct numerical simulations (QDNS), which sample the response of near-wall turbulence…

流体动力学 · 物理学 2017-10-20 Neil D. Sandham , Roderick Johnstone , Christian T. Jacobs

A fully-convolutional neural-network model is used to predict the streamwise velocity fields at several wall-normal locations by taking as input the streamwise and spanwise wall-shear-stress planes in a turbulent open channel flow. The…

流体动力学 · 物理学 2020-08-26 L. Guastoni , M. P. Encinar , P. Schlatter , H. Azizpour , R. Vinuesa

Global stability analysis and direct numerical simulation (DNS) are performed to study boundary layer flows with an isolated roughness element. Wall-attached cuboids with aspect ratios $\eta=1$ and $\eta=0.5$ are investigated for fixed…

流体动力学 · 物理学 2022-10-05 Rong Ma , Krishnan Mahesh

A fully-resolved direct-numerical-simulation (DNS) approach for investigating flexible bodies forced by a turbulent incoming flow is designed to study the flapping motion of a flexible flag at moderate Reynolds number. The incoming…

流体动力学 · 物理学 2021-08-25 Stefano Olivieri , Francesco Viola , Andrea Mazzino , Marco E. Rosti

We revisit the grid-point requirement estimates in Choi and Moin [Phys. Fluid, 24, 011702 (2012)] and establish more general grid-point requirements for direct numerical simulations (DNS) and large-eddy simulations (LES) of a spatially…

流体动力学 · 物理学 2021-06-16 Xiang I. A. Yang , Kevin Patrick Griffin

In this work, important two-phase flow scalings are derived, which enable the quantification of grid-point and time-step requirements as functions of Re, We, and Ca numbers. The adequate grid resolution is determined in the…

流体动力学 · 物理学 2025-10-10 Luis H. Hatashita , Pranav Nathan , Suhas S. Jain

Insufficient numerical resolution of grid-based, direct numerical simulations (DNS) hampers the development of instabilitydriven turbulence at small (unresolved) scales. As an alternative to DNS, sub-grid models can potentially reproduce…

高能天体物理现象 · 物理学 2022-10-26 Miquel Miravet-Tenés , Pablo Cerdá-Durán , Martin Obergaulinger , José A. Font

The turbulent boundary layer over a flat plate is computed by direct numerical simulation (DNS) of the incompressible Navier-Stokes equations as a test bed for a synthetic turbulence generator (STG) inflow boundary condition. The inlet…

流体动力学 · 物理学 2021-02-15 James R. Wright , Riccardo Balin , John W. Patterson , John A. Evans , Kenneth E. Jansen

The effect of grid resolution on large eddy simulation (LES) of wall-bounded turbulent flow is investigated. A channel flow simulation campaign involving systematic variation of the streamwise ($\Delta x$) and spanwise ($\Delta z$) grid…

流体动力学 · 物理学 2018-05-23 Saleh Rezaeiravesh , Mattias Liefvendahl

A direct numerical simulation (DNS) of a channel flow with one curved surface was performed at moderate Reynolds number (Re_tau = 395 at the inlet). The adverse pressure gradient was obtained by a wall curvature through a mathematical…

流体动力学 · 物理学 2017-11-22 Matthieu Marquillie , Jean-Philippe Laval , Rostislav Dolganov

Direct Numerical Simulations (DNS) of turbulent channel flow at a shear Reynolds number of $Re_{*}=360$ for Newtonian and Herschel-Bulkley fluids in smooth and rough channels has been performed. The rough surface was made of irregular…

流体动力学 · 物理学 2023-12-11 C. Narayanan , S. Nauer , J. -S. Singh , R. Belt , T. Palermo , D. Lakehal

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…

流体动力学 · 物理学 2020-12-04 Satoshi Miyazaki , Yuji Hattori

The turbulent/non-turbulent interface is analysed in a direct numerical simulation of a boundary layer in the range $Re_\theta=2800-6600$, with emphasis on the behaviour of the relatively large-scale fractal intermittent region. This…

流体动力学 · 物理学 2017-10-23 Guillem Borrell , Javier Jiménez

Results of numerical simulations obtained by a staggered finite difference scheme together with an efficient immersed boundary method are presented to understand the effects of the shape of three-dimensional obstacles on the transition of a…

流体动力学 · 物理学 2015-03-31 Paolo Orlandi , Sergio Pirozzoli , Matteo Bernardini

We study the error scaling properties of large-eddy simulation (LES) in the outer region of wall-bounded turbulence at moderately high Reynolds numbers. In order to avoid the additional complexity of wall-modeling, we perform LES of…

流体动力学 · 物理学 2021-10-26 Adrián Lozano-Durán , Hyunji Jane Bae

A Full Turbulence Simulation (FTS) of turbulent channel flow at friction Reynolds number (Re_tau) approx 1000 was performed by resolving the Kolmogorov wavenumber in all spatial directions. At this Reynolds number, the intermediate layer…

流体动力学 · 物理学 2026-05-22 Yoshinobu Yamamoto , Yoshiyuki Tsuji

The predictive accuracy of wall-modelled LES is influenced by a combination of the subgrid model, the wall model, the numerical dissipation induced primarily by the convective numerical scheme, and also by the density and topology of the…

流体动力学 · 物理学 2020-09-02 Timofey Mukha , Rickard E. Bensow , Mattias Liefvendahl

We focus in this paper on the effect of the resolution of Direct Numerical Simulations (DNS) on the spatio-temporal development of the turbulence downstream of a single square grid. The aims of this study are to validate our numerical…

流体动力学 · 物理学 2015-10-28 S. Laizet , J. Nedić , J. C. Vassilicos

Modelling the near-wall region of wall-bounded turbulent flows is a widespread practice to reduce the computational cost of large-eddy simulations (LESs) at high Reynolds number. As a first step towards a data-driven wall-model, a…

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'.…

流体动力学 · 物理学 2025-12-04 Zishuo Han , Weiyu Shen , Yue Yang
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