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相关论文: Large-eddy simulation of separated flows on unconv…

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This paper introduces a new approach to Large-Eddy Simulation (LES) where subgrid-scale (SGS) dissipation is applied proportionally to the degree of local spectral broadening, hence mitigated or deactivated in regions dominated by…

计算工程、金融与科学 · 计算机科学 2018-02-14 Jean-Baptiste Chapelier , Bono Wasistho , Carlo Scalo

Predictive simulations of complex systems are essential for applications ranging from weather forecasting to drug design. The veracity of these predictions hinges on their capacity to capture the effective system dynamics. Massively…

计算物理 · 物理学 2021-10-20 Pantelis R. Vlachas , Georgios Arampatzis , Caroline Uhler , Petros Koumoutsakos

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

The $\alpha$-modeling strategy is followed to derive a new subgrid parameterization of the turbulent stress tensor in large-eddy simulation (LES). The LES-$\alpha$ modeling yields an explicitly filtered subgrid parameterization which…

混沌动力学 · 物理学 2007-05-23 Bernard J. Geurts , Darryl D. Holm

This work examines the flow separation and the resulting pressure distortions at the exit plane of a serpentine diffuser operating at both subsonic and transonic conditions. Wallmodeled large-eddy simulations (WMLES) using the charLES flow…

流体动力学 · 物理学 2025-06-19 Rahul Agrawal , Chad Winkler , Sanjeeb Bose , Parviz Moin

The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulence, viz. large eddy simulations (LES), hybrid…

流体动力学 · 物理学 2023-01-25 Aniruddhe Pradhan , Karthik Duraisamy

Large Eddy Simulations (LES) are becoming increasingly viable due to the growth in computational power the last few decades, and subgrid stress modelling plays a large role in the accuracy of LES. A new class of neural network models, S4…

流体动力学 · 物理学 2025-11-17 Andy Wu , Sanjiva K. Lele

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

Approximate Deconvolution (AD) has emerged as a promising closure for Large-Eddy Simulation (LES) in complex multi-physics flows, where the conventional pure Dynamic Eddy-Viscosity (DEV) models experience issues. In this research, we…

流体动力学 · 物理学 2025-11-14 Ehsan Amani , Mohammad Bagher Molaei , Morteza Ghorbani

In meandering rivers, interactions between flow, sediment transport, and bed topography affect diverse processes, including bedform development and channel migration. Predicting how these interactions affect the spatial patterns and…

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

Solving the Reynolds-averaged Navier-Stokes equations (RANS) closed with an eddy viscosity computed through a turbulence model is still the leading approach for Computational Fluid Dynamics simulations. Unfortunately, universal models with…

流体动力学 · 物理学 2025-09-18 Marco Castelletti , Maurizio Quadrio

The goal of this paper is twofold: first, it investigates the effect of low-pass spatial filters for approximate deconvolution large eddy simulation (AD-LES) of turbulent incompressible flows. Second, it proposes the hyper-differential…

流体动力学 · 物理学 2018-01-29 Omer San , Anne E. Staples , Traian Iliescu

The development of a reliable subgrid-scale (SGS) model for large-eddy simulation (LES) is of great importance for many scientific and engineering applications. Recently, deep learning approaches have been tested for this purpose using…

流体动力学 · 物理学 2022-11-09 Junhyuk Kim , Hyojin Kim , Jiyeon Kim , Changhoon Lee

In this work we will identify a novel relation between Smoothed Particle Hydrodynamics (SPH) and explicit Large Eddy Simulation (LES) using a coarse-graining method from Non-Equilibrium Molecular Dynamics (NEMD). While the current…

流体动力学 · 物理学 2022-11-24 Max Okraschevski , Niklas Bürkle , Rainer Koch , Hans-Jörg Bauer

Grid adaptation for implicit Large Eddy Simulation (LES) is a non-trivial challenge due to the inherent coupling of the modeling and numerical errors. An attempt to address the challenge first requires a comprehensive assessment and then…

数值分析 · 数学 2020-11-09 Yao Jiang , Siva Nadarajah

The prediction of statistical properties of turbulent flow in large-scale rivers is important for river flow analysis. Large-eddy simulations (LESs) provide a powerful tool for such predictions, however, they require a very long sampling…

流体动力学 · 物理学 2021-06-22 Zexia Zhang , Kevin Flora1 , Seokkoo Kang , Ajay B. Limaye , Ali Khosronejad

The present study is concerned with large-eddy simulations (LES) of supersonic jet flows. The work addresses, in particular, the simulation of a perfectly expanded free jet flow with an exit Mach number of 1.4 and an exit temperature equal…

流体动力学 · 物理学 2023-01-05 D. F. Abreu , C. Junqueira-Junior , E. T. Dauricio , J. L. F. Azevedo

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising…

流体动力学 · 物理学 2022-03-14 Ryley McConkey , Eugene Yee , Fue-Sang Lien

One issue associated with the use of Large-Eddy Simulation (LES) to investigate the dispersion of small inertial particles in turbulent flows is the accuracy with which particle statistics and concentration can be reproduced. The motion of…