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The rational large eddy simulation (RLES) model is applied to turbulent channel flows. This approximate deconvolution model is based on a rational (subdiagonal Pade') approximation of the Fourier transform of the Gaussian filter and is…

数值分析 · 数学 2025-10-20 T. Iliescu , P. Fischer

We put forth a dynamic modeling framework for sub-grid parametrization of large eddy simulation of turbulent flows based upon the use of the approximate deconvolution procedure to compute the Smagorinsky constant self-adaptively from the…

流体动力学 · 物理学 2016-05-02 Romit Maulik , Omer San

We propose a framework for developing wall models for large-eddy simulation that is able to capture pressure-gradient effects using multi-agent reinforcement learning. Within this framework, the distributed reinforcement learning agents…

流体动力学 · 物理学 2024-07-29 Di Zhou , H. Jane Bae

Direct numerical simulations of the incompressible Navier-Stokes equations are not feasible yet for most practical turbulent flows. Therefore, dynamically less complex mathematical formulations are necessary for coarse-grained simulations.…

流体动力学 · 物理学 2017-12-04 F. X. Trias , A. Gorobets , M. H. Silvis , R. W. C. P. Verstappen , A. Oliva

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

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 original goal of Large Eddy Simulations of fully developed turbulent flows was to accurately describe large-scale flow features ${\bf u}(\Delta)$ at the scales $r\geq \Delta$ where $\Delta$ is a size of computational mesh. The effect of…

流体动力学 · 物理学 2011-09-29 Victor Yakhot , John Wanderer

Predicting the large-scale dynamics of three-dimensional (3D) turbulence is challenging for machine learning approaches. This paper introduces a transformer-based neural operator (TNO) to achieve precise and efficient predictions in the…

流体动力学 · 物理学 2024-06-07 Zhijie Li , Tianyuan Liu , Wenhui Peng , Zelong Yuan , Jianchun Wang

One of the greatest challenges to using large-eddy simulations (LES) in engineering applications is the large number of grid points required near walls. To mitigate this issue, researchers often couple LES with a simplified model of the…

流体动力学 · 物理学 2016-11-15 Alexandre Marques , Qiqi Wang , Johan Larsson , Gregory Laskowski , Sanjeeb Bose

A previously developed modeling procedure for large eddy simulations (LESs) is extended to allow physical space implementations for inhomogeneous flows. The method is inspired by the well-established theoretical analyses and numerical…

流体动力学 · 物理学 2022-10-28 Guangrui Sun , J. Andrzej Domaradzki

In atmospheric and turbulent flow modeling, Large Eddy Simulation (LES) is often used to reduce computational cost, while observational data typically originates from the underlying physical system. Motivated by this setting, we study a…

偏微分方程分析 · 数学 2025-08-12 Adam Larios , Ali Pakzad , Nicholas White

A promising and cost-effective method for numerical simulation of high Re wall-bounded flows is wall-modeled large-eddy simulation. Most wall models are formulated from the Reynolds-averaged Navier-Stokes equations (RANS). These RANS-based…

流体动力学 · 物理学 2021-01-08 Ahmed Elnahhas , Adrián Lozano-Durán , Parviz Moin

An analysis of the turbulence-radiation interaction in the framework of large eddy simulation (LES) is presented. Direct numerical simulation (DNS) of statistical steady forced homogeneous isotropic turbulence is used to evaluate the…

流体动力学 · 物理学 2019-03-14 Maxime Roger , Pedro Coelho , Carlos Da Silva

Large Eddy Simulation (LES) with dynamic Smagorinsky model has been applied to numerically investigate the complicated flow structures that evolve in the near wake of a cylindrical after body aligned with a uniform Mach 2.46 flow. Mean flow…

流体动力学 · 物理学 2021-02-16 Pratik Das , Ashoke De

For high-fidelity predictions of turbulent flows in complex practical engineering problems, the Wall-Modeled (WM) Large-Eddy Simulation (LES) has aroused great interest. In the present study, we prove that the conventional Wall-Stress…

流体动力学 · 物理学 2025-11-12 Mohammad Taghvaei , Ehsan Amani

Large eddy simulation (LES) of turbulence in complex geometries and domains is often conducted with high aspect ratio resolution cells of varying shapes and orientations. The effects of such anisotropic resolution are often simplified or…

流体动力学 · 物理学 2019-11-20 Sigfried Haering , Myoungkyu Lee , Robert D. Moser

Numerical prediction of the interactions between wind and ocean waves is essential for climate modeling and a wide range of offshore operations. Large Eddy Simulation (LES) of the marine atmospheric boundary layer is a practical numerical…

流体动力学 · 物理学 2024-09-06 Manuel Ayala , Zein Sadek , Ondřej Ferčák , Raúl Bayoán Cal , Dennice Gayme , Charles Meneveau

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

A large eddy simulation wall model is developed based on a formal interpretation of quasi-equilibrium that governs the momentum balance integrated in the wall-normal direction. The model substitutes the law-of-the-wall velocity profile for…

流体动力学 · 物理学 2022-02-02 Mitchell Fowler , Tamer A. Zaki , Charles Meneveau

We continue a previous work in which {\em a priori} estimates were derived on subgrid stress and subgrid flux for filtering schemes used in the turbulence modelling method of Large-Eddy Simulation (LES). The estimates were derived there as…

chao-dyn · 物理学 2008-02-03 Gregory L. Eyink