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The three-dimensional Time-Resolved Lagrangian Particle Tracking (3D TR-LPT) technique has recently advanced flow diagnostics by providing high spatiotemporal resolution measurements under the Lagrangian framework. To fully exploit its…

流体动力学 · 物理学 2023-08-21 Lanyu Li , Zhao Pan

In this paper we propose a new modeling framework for large eddy simulations (LES) of particle-laden turbulent flows that captures the interaction between the particle and fluid phase on both the resolved and subgrid-scales. Unlike the vast…

流体动力学 · 物理学 2023-10-26 Max Hausmann , Fabien Evrard , Berend van Wachem

Wall-modeled large-eddy simulation (WMLES) is widely recognized as a useful method for simulation of turbulent flows at high Reynolds numbers. Nevertheless, a continual issue in different wall models is the shift of the mean velocity…

流体动力学 · 物理学 2024-11-20 Huan-Cong Liu , Chun-Xiao Xu , Wei-Xi Huang

By combining AI and fluid physics, we discover a closed-form closure for 2D turbulence from small direct numerical simulation (DNS) data. Large-eddy simulation (LES) with this closure is accurate and stable, reproducing DNS statistics…

大气与海洋物理 · 物理学 2026-01-21 Karan Jakhar , Yifei Guan , Pedram Hassanzadeh

A large eddy simulation (LES) with an extended Smagorinsky model has been carried to investigate numerically the fully developed turbulent flow of a shear thinning fluid (n=0.75) in a stationary pipe at a simulation's Reynolds number equals…

流体动力学 · 物理学 2020-06-01 Mohamed Abdi , Meryem Ould-Rouiss , Abdelkader Noureddine

We conducted WMLES to examine the performance of a simple and widely used ODE-based equilibrium wall model in a spatially-developing 3D TBL inside a bent square duct (Schwarz and Bradshaw 1994) and 3D separated flows behind a skewed bump…

流体动力学 · 物理学 2020-01-07 Minjeong Cho , George I. Park , Adrián Lozano-Durán , Parviz Moin

We investigate statistics of large-scale structures from large-eddy simulation (LES) of turbulent channel flow at friction Reynolds numbers $Re_\tau = 2 {\rm k}$ and $200 {\rm k}$. To properly capture the behaviour of large-scale…

流体动力学 · 物理学 2015-05-18 D. Chung , B. J. McKeon

This paper proposes a new data assimilation method for recovering high fidelity turbulent flow field around airfoil at high Reynolds numbers based on experimental data, which is called Proper Orthogonal Decomposition Inversion…

流体动力学 · 物理学 2020-07-14 Yilang Liu , Weiwei Zhang

Turbulent flow has been extensively studied using computational fluid dynamics (CFD) simulations since turbulent flow regime is so frequently encountered in both academic and engineering applications. The high-fidelity simulation of the…

流体动力学 · 物理学 2024-05-21 Minghan Chu

In this study, we conduct a parametric analysis to evaluate the sensitivities of wall-modeled large-eddy simulation (LES) with respect to subgrid-scale (SGS) models, mesh resolution, wall boundary conditions and mesh anisotropy. While such…

流体动力学 · 物理学 2024-03-26 Di Zhou , H. Jane Bae

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 logarithmic law for the mean velocity in turbulent boundary layers has long provided a valuable and robust reference for comparison with theories, models, and large-eddy simulations (LES) of wall-bounded turbulence. More recently,…

流体动力学 · 物理学 2014-12-23 Richard J. A. M. Stevens , Michael Wilczek , Charles Meneveau

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

We present large-eddy-simulation (LES) modeling approaches for the simulation of atmospheric boundary layer turbulence that are of direct relevance to wind energy production. In this paper, we study a GABLS benchmark problem using…

计算工程、金融与科学 · 计算机科学 2024-10-02 Ananias Tomboulides Matthew Churchfield , Paul Fischer , Michael Sprague , Misun Min

The dynamic model for large-eddy simulation (LES) of turbulent flows requires test filtering the resolved velocity fields in order to determine model coefficients. However, test filtering is costly to perform in large-eddy simulation of…

流体动力学 · 物理学 2009-11-07 Stuart Chester , Fabrice Charlette , Charles Meneveau

In turbulence research and flow applications, turbulence models like RaNS (Reynolds averaged Navier-Stokes) models and LES (Large Eddy Simulation) are used. Both models filter the governing flow equations. Thus a scale separation approach…

流体动力学 · 物理学 2015-06-17 Christoph Glawe , Heiko Schmidt , Alan R. Kerstein , Rupert Klein

This work presents a feature-rich open-source library for wall-modelled large-eddy simulation (WMLES), which is a turbulence modelling approach that reduces the computational cost of traditional (wall-resolved) LES by introducing special…

流体动力学 · 物理学 2019-04-01 Timofey Mukha , Saleh Rezaeiravesh , Mattias Liefvendahl

We study the numerical errors of large-eddy simulation (LES) in isotropic and wall-bounded turbulence. A direct-numerical-simulation (DNS)-aided LES formulation, where the subgrid-scale (SGS) term of the LES is computed by using filtered…

流体动力学 · 物理学 2022-08-05 H. Jane Bae , Adrian Lozano-Duran

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive 3D density measurements of turbulence. Wavefront tomography is a technique…

信号处理 · 电气工程与系统科学 2026-02-19 Karl J. Weisenburger , Gregery T. Buzzard , Charles A. Bouman , Matthew R. Kemnetz

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