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We conduct wall-modeled LES (WMLES) of a pressure-driven three-dimensional turbulent boundary layer (3DTBL) developing on the floor of a bent square duct to investigate the predictive capability of three widely used wall models, namely, a…

流体动力学 · 物理学 2023-04-26 Xiaohan Hu , Imran Hayat , George Ilhwan Park

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

In this work, a non-equilibrium wall model is proposed for the prediction of turbulent flows experiencing adverse pressure gradients, including separated flow regimes. The mean-flow nonequilibrium is identified by comparing two…

流体动力学 · 物理学 2024-07-17 Rahul Agrawal , Sanjeeb T. Bose , Parviz Moin

This article proposes a Reynolds number scaling of the required grid points to perform wall-modeled LES of turbulent flows encountering separation off a solid surface. Based on comparisons between the various time scales in a…

流体动力学 · 物理学 2024-01-02 Rahul Agrawal , Sanjeeb Bose , Parviz Moin

Very recently, a defect model which depicts the growth tendency of the near-wall peak of the streamwise turbulence intensity has been developed (Chen $\&$ Sreenivasan, J. Fluid Mech. (2021), vol.908, R3). Based on the finiteness of the…

流体动力学 · 物理学 2023-03-30 Cheng Cheng , Lin Fu

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

This study uses high-fidelity simulations (DNS or LES) and experimental datasets to analyse the effect of non-equilibrium streamwise mean pressure gradients (adverse or favourable), including attached and separated flows, on the statistics…

流体动力学 · 物理学 2024-11-20 Saurabh Pargal , Junlin Yuan , Stephane Moreau

Wall-pressure fluctuations are a practically robust input for real-time control systems aimed at modifying wall-bounded turbulence. The scaling behaviour of the wall-pressure--velocity coupling requires investigation to properly design a…

流体动力学 · 物理学 2024-01-11 Woutijn J. Baars , Giulio Dacome , Myoungkyu Lee

A new approach to turbulence simulation, based on a combination of large-eddy simulation (LES) for the whole flow and an array of non-space-filling quasi-direct numerical simulations (QDNS), which sample the response of near-wall turbulence…

流体动力学 · 物理学 2017-10-20 Neil D. Sandham , Roderick Johnstone , Christian T. Jacobs

We study the laminar and turbulent channel flow over a viscous hyper-elastic wall and show that it is possible to sustain an unsteady chaotic turbulent-like flow at any Reynolds number by properly choosing the wall elastic modulus. We…

流体动力学 · 物理学 2020-08-05 Marco E Rosti , Luca Brandt

Direct Numerical Simulations (DNS) of turbulent channel flow at a shear Reynolds number of $Re_{*}=360$ for Newtonian and Herschel-Bulkley fluids in smooth and rough channels has been performed. The rough surface was made of irregular…

流体动力学 · 物理学 2023-12-11 C. Narayanan , S. Nauer , J. -S. Singh , R. Belt , T. Palermo , D. Lakehal

Wall-models are essential for enabling large-eddy simulations (LESs) of realistic problems at high Reynolds numbers. The present study is focused on approaches that directly model the wall shear stress, specifically on filling the gap…

流体动力学 · 物理学 2015-12-01 Stefan Hickel , Emile Touber , Julien Bodart , Johan Larsson

Wall modelling in large-eddy simulation (LES) is necessary to overcome the prohibitive near-wall resolution requirements in high-Reynolds-number turbulent flows. Most existing wall models rely on assumptions about the state of the boundary…

流体动力学 · 物理学 2021-10-26 H. Jane Bae , Adrián Lozano-Durán , Sanjeeb T. Bose , Parviz Moin

Knowledge of turbulent flows over non-flat surfaces is of major practical interest in diverse applications. Significant work continues to be reported in the roughness regime at high Reynolds numbers where the cumulative effect of surface…

流体动力学 · 物理学 2019-11-27 Balaji Jayaraman , Saadbin Khan

Wall-bounded turbulence is relevant for many engineering and natural science applications, yet there are still aspects of its underlying physics that are not fully understood, particularly at high Reynolds numbers. In this study, we…

流体动力学 · 物理学 2024-04-04 Himani Garg , Lei Wang , Martin Andersson , Christer Fureby

A new scaling is derived that yields a Reynolds number independent profile for all components of the Reynolds stress in the near-wall region of wall bounded flows, including channel, pipe and boundary layer flows. The scaling demonstrates…

流体动力学 · 物理学 2024-02-06 Alexander J. Smits , Marcus Hultmark , Myoungkyu Lee , Sergio Pirozzoli , Xiaohua Wu

Using the Lagrangian transport of momentum, the Reynolds stress can be expressed in terms of basic turbulence parameters. The Reynolds stress gradient represents the lateral transport of stream-wise momentum, balanced by the u2 transport,…

流体动力学 · 物理学 2019-12-11 T. -W. Lee

Modeling of wall-bounded turbulent flows is still an open problem in classical physics, with only modest progress made in the last few decades beyond the so-called `log law', which describes only the intermediate region in wall-bounded…

流体动力学 · 物理学 2018-08-31 Fangying Song , George Em Karniadakis

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

The variance and spectra of wall-normal velocities are investigated for direct numerical simulations of turbulent flow in a channel, pipe, and zero-pressure-gradient boundary layer across a decade of friction Reynolds numbers. Spectra along…

流体动力学 · 物理学 2026-04-22 Michael Heisel , Rahul Deshpande , Gabriel G. Katul
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