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The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for various flow problems. A guided diffusion…

Large Eddy Simulation (LES) is a very useful tool when simulating turbulent flows if we are only interested in its "larger" scales. One of the possible ways to derive the LES equations is to apply a filter operator to the Navier-Stokes…

偏微分方程分析 · 数学 2017-03-14 José M. Rodríguez , Raquel Taboada-Vázquez

This work presents a review and perspectives on recent developments in the use of machine learning (ML) to augment Reynolds-averaged Navier--Stokes (RANS) and Large Eddy Simulation (LES) models of turbulent flows. Different approaches of…

流体动力学 · 物理学 2021-05-19 Karthik Duraisamy

The present study revisits the amplitude modulation phenomenon, specifically for the robustness in its quantification. To achieve this, a well-resolved large-eddy simulation (LES) data set at Re_theta= 8200 is used. First, the fluctuating…

流体动力学 · 物理学 2018-12-11 E. Dogan , R. Örlü , D. Gatti , R. Vinuesa , P. Schlatter

Extensive experimental evidence highlight that scalar turbulence exhibits anomalous diffusion and stronger intermittency levels at small scales compared to that in fluid turbulence. This renders the corresponding subgrid-scale dynamics…

流体动力学 · 物理学 2024-06-19 S. Hadi Seyedi , Ali Akhavan-Safaei , Mohsen Zayernouri

This article utilizes the Large-Eddy Simulation (LES) paradigm with a physics-based turbulence modeling approach, including a dynamic subgrid-scale model and an equilibrium wall model, to examine the flow over the NASA transonic Common…

流体动力学 · 物理学 2024-07-11 Konrad A. Goc , Rahul Agrawal , Sanjeeb T. Bose , Parviz Moin

The immense computational cost of simulating turbulence has motivated the use of machine learning approaches for super-resolving turbulent flows. A central challenge is ensuring that learned models respect physical symmetries, such as…

流体动力学 · 物理学 2025-09-26 Julia Balla , Jeremiah Bailey , Ali Backour , Elyssa Hofgard , Tommi Jaakkola , Tess Smidt , Ryley McConkey

The simulation of high Reynolds number (Re) separated turbulent flows faces significant problems for decades: large eddy simulation (LES) is computationally too expensive, and Reynolds-averaged Navier-Stokes (RANS) methods and hybrid…

流体动力学 · 物理学 2024-12-02 Stefan Heinz , Adeyemi Fagbade

We propose a new model of turbulence for use in large-eddy simulations (LES). The turbulent force, represented here by the turbulent Lamb vector, is divided in two contributions. The contribution including only subfilter fields is…

流体动力学 · 物理学 2009-11-11 Jean-Philippe Laval , Berengere Dubrulle

The shock induced mixing of two gases separated by a perturbed interface is investigated through Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). In a simulation, physical dissipation of the velocity field and species mass…

流体动力学 · 物理学 2015-06-18 Britton J. Olson , Jeffrey A. Greenough

Climate change necessitates rapid expansion of renewable energy, with wind energy offering a scalable and low-impact solution. However, accurate prediction of wind loads and power generation remains challenging due to uncertainties in wind…

流体动力学 · 物理学 2026-04-30 Omar Sallam , Mirjam Fürth

A computational domain translation velocity is often used in LES simulations to improve computational performance by allowing longer time-step intervals. Even though the equations of motion are Galilean invariant, LES results have been…

大气与海洋物理 · 物理学 2019-07-15 Oumaima Lamaakel , Georgios Matheou

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

Kolmogorov's (1941) theory of self-similarity implies the universality of small-scale eddies, and holds promise for a universal sub-grid scale model for large eddy simulation. The fact is the empirical coefficient of a typical sub-grid…

流体动力学 · 物理学 2022-11-24 Jinglei Xu , Qi Li , Xianxu Yuan , Lin Bi , Pengxin Liu , Jianqiang Chen

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

The present work is concerned with a study of large eddy simulations (LES) of unsteady turbulent jet flows. In particular, the present analysis is focused on the effects of the subgrid-scale modeling used when a second-order spatial…

流体动力学 · 物理学 2022-12-26 Carlos Junqueira-Junior , Sami Yamouni , João Luiz F. Azevedo , William R. Wolf

Predictive simulation of many complex flows requires moving beyond Reynolds-averaged Navier-Stokes (RANS) based models to representations resolving at least some scales of turbulence in at least some regions of the flow. To resolve…

流体动力学 · 物理学 2018-12-11 Sigfried Haering , Todd A. Oliver , Robert D. Moser

We study the dispersion characteristics of slightly buoyant droplets in a turbulent jet using large eddy simulations (LES). The droplet number density fields are represented using an Eulerian approach with the dispersed phase modelled using…

流体动力学 · 物理学 2022-02-09 Aditya Aiyer , Charles Meneveau

In this study, ensembles of experimental data are presented and utilized to compare and validate two models used in the simulation of variable density, compressible turbulent mixing. Though models of this kind (Reynolds Averaged Navier…

流体动力学 · 物理学 2022-03-07 Benjamin Musci , Britton Olson , Samuel Petter , Gokul Pathikonda , Devesh Ranjan

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