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相关论文: Characterizing Turbulence at a Forest Edge: Compar…

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Large-eddy simulations (LES) with an appropriate subgrid-scale (SGS) model provide a powerful tool for investigating real-world turbulence. The Smagorinsky model, one of the simplest and most used SGS models, often shows an over-dissipative…

流体动力学 · 物理学 2026-03-30 Nobumitsu Yokoi , Pablo D. Mininni , Annick Pouquet , Duane Rosenberg , Raffaele Marino

Large eddy simulation allows to incorporate the important driving physics of turbulent flow through forest- or vegetation-like canopies. In this paper we investigate the effects of vortex stretching and coherent structures on the…

流体动力学 · 物理学 2020-10-06 Md. Abdus Samad Bhuiyan , Jahrul M Alam

In the field of Large Eddy Simulation, the Smagorinsky subgrid scale model (in some form) is the most commonly accepted and used subgrid scale model. The purpose of this paper is to address the main weakness of the Smagorinsky model, its…

数值分析 · 数学 2025-10-20 Tommy Kunhung Kim

The results of large eddy simulation (LES) using three sub-grid scale models, namely: constant coefficient Smagorinsky, dynamic Smagorinsky, and a dynamic Clark model, for rotating stratified turbulence in the absence of forcing using…

流体动力学 · 物理学 2023-08-17 Kiran Jadhav , Rahul Agrawal , Abhilash J. Chandy

Most sub-grid scale (SGS) models employed in LES (large eddy simulation) formulations were originally developed for incompressible, single phase, inert flows and assume transfer of energy based on the classical energy cascade mechanism.…

流体动力学 · 物理学 2023-09-13 Jhon Cordova , Cesar Celis , Andres Mendiburu , Luis Bravo , Prashant Khare

Traditional large eddy simulation is based on Kolmogrov's hypothesis, and done in the inertial range. In inertial range the LES model coefficient is scale-invariant. In many cases, such as computing in the boundary layer, the filter scale…

流体动力学 · 物理学 2014-08-18 Changping Yu

Large-eddy simulations of the turbulent flow in a lid-driven cubical cavity have been carried out at a Reynolds number of 12000 using spectral element methods. Two distinct subgrid-scales models, namely a dynamic Smagorinsky model and a…

流体动力学 · 物理学 2007-09-04 Roland Bouffanais , Michel O. Deville , Emmanuel Leriche

This paper presents a rigorous theoretical extension of the Smagorinsky model for turbulence simulations. The author builds on its fundamental framework, addressing known limitations, and making new mathematical advances. Specifically, this…

流体动力学 · 物理学 2024-11-19 Rômulo Damasclin Chaves dos Santos

The Large Eddy Simulation (LES) approach is adapted to the study of plasma microturbulence in a fully three-dimensional gyrokinetic system. Ion temperature gradient driven turbulence is studied with the {\sc GENE} code for both a standard…

等离子体物理 · 物理学 2015-03-19 P. Morel , A. Bañón Navarro , M. Albrecht-Marc , D. Carati , F. Merz , T. Görler , F. Jenko

When simulating multiscale systems, where some fields cannot be fully prescribed despite their effects on the simulation's accuracy, closure models are needed. This phenomenon is observed in turbulent fluid dynamics, where Large Eddy…

流体动力学 · 物理学 2025-12-01 Eduardo Vital , Jean-Marc Gratien , Yassine Ayoun , Thibault Faney , Julien Bohbot

In large-eddy simulations, subgrid-scale (SGS) processes are parameterized as a function of filtered grid-scale variables. First-order, algebraic SGS models are based on the eddy-viscosity assumption, which does not always hold for…

A shear-improved Smagorinsky model is introduced based on recent results concerning shear effects in wall-bounded turbulence by Toschi et al. (2000). The Smagorinsky eddy-viscosity is modified subtracting the magnitude of the mean shear…

混沌动力学 · 物理学 2015-06-26 E. Leveque , F. Toschi , L. Shao , J. -P. Bertoglio

Turbulence models, such as the Smagorinsky model herein, are used to represent the energy lost from resolved to under-resolved scales due to the energy cascade (i.e. non-linearity). Analytic estimates of the energy dissipation rates of a…

数值分析 · 数学 2019-04-24 Ali Pakzad

In high Reynolds number turbulent flows, energy dissipation refers to the process of energy transfer from kinetic energy to internal energy due to molecular viscosity. In large eddy simulation (LES) with one-equation turbulence models, the…

流体动力学 · 物理学 2020-01-22 Hongjiang Li , Christopher J. Rutland , Francisco E. Hernandez Perez , Hong G. Im

In this review, the methodology of large eddy simulations (LES) is introduced and applications in astrophysics are discussed. As theoretical framework, the scale decomposition of the dynamical equations for neutral fluids by means of…

宇宙学与河外天体物理 · 物理学 2014-04-10 Wolfram Schmidt

Direct and large eddy simulations of hydrodynamic and hydromagnetic turbulence have been performed in an attempt to isolate artifacts from real and possibly asymptotic features in the energy spectra. It is shown that in a hydrodynamic…

天体物理学 · 物理学 2007-05-23 N. E. L. Haugen , A. Brandenburg

A new tuning-free subgrid-scale model, termed `locally-averaged scale-dependent dynamic' (LASDD) model, is developed and implemented in large-eddy simulations (LESs) of stable boundary layers. The new model dynamically computes the…

大气与海洋物理 · 物理学 2016-08-16 Sukanta Basu , Fernando Porté-Agel

This study develops invariance-embedded machine learning sub-grid-scale (SGS) stress models admitting turbulence kinetic energy (TKE) backscatter towards more accurate large eddy simulation (LES) of meso-scale turbulent hurricane boundary…

流体动力学 · 物理学 2025-04-22 Md Badrul Hasan , Meilin Yu , Tim Oates

The Smagorinsky model, unmodified, is often reported to severely overdiffuse flows. Previous estimates of the energy dissipation rate of the Smagorinsky model for shear flows reflect a blow up of model energy dissipation as Re increases.…

数值分析 · 数学 2016-01-26 William Layton

A new methodology based on energy flux similarity is suggested in this paper for large eddy simulation (LES) of transitional and turbulent flows. Existing knowledge reveals that the energy cascade generally exists in transitional and…

流体动力学 · 物理学 2019-10-31 Han Qi , Xinliang Li , Hao Zhou , Changping Yu
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