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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

Homogeneous anisotropic turbulence simulations are used to determine off-diagonal components of the Reynolds stress tensor and its parameterization in terms of turbulent viscosity and Lambda-effect. The turbulence is forced in an…

天体物理学 · 物理学 2011-11-10 P. J. Käpylä , A. Brandenburg

A new model for the "rapid" part of the velocity/pressure-gradient correlation in the Reynolds averaged Navier-Stokes equations is suggested. It is shown that in an inhomogeneous incompressible turbulent flow, the model that is linear in…

流体动力学 · 物理学 2007-05-23 Svetlana V. Poroseva

Using the Lagrangian transport of momentum, the Reynolds shear stress can be expressed in terms of basic turbulence parameters. In this view, the Reynolds stress gradient represents the lateral transport of streamwise momentum, balanced by…

流体动力学 · 物理学 2020-07-28 T. -W. Lee

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 the present study, we conduct direct numerical simulations to investigate the near-wall dynamics of compressible turbulent boundary layers at the free-stream Mach number of 6 laden with heavy particles. By inspecting the instantaneous…

流体动力学 · 物理学 2025-05-14 Ming Yu , Lihao Zhao , Yibin Du , Xianxu Yuan , Chunxiao Xu

A realistic inflow boundary condition is essential for successful simulation of the developing turbulent boundary layer or channel flows. Recent advances in artificial intelligence (AI) have enabled the development of an inflow generator…

流体动力学 · 物理学 2020-02-19 Junhyuk Kim , Changhoon Lee

A deep learning (DL) closure model for large-eddy simulation (LES) is developed and evaluated for incompressible flows around a rectangular cylinder at moderate Reynolds numbers. Near-wall flow simulation remains a central challenge in…

流体动力学 · 物理学 2023-07-19 Justin Sirignano , Jonathan F. MacArt

Turbulence modeling is a classical approach to address the multiscale nature of fluid turbulence. Instead of resolving all scales of motion, which is currently mathematically and numerically intractable, reduced models that capture the…

流体动力学 · 物理学 2018-12-10 Rui Fang , David Sondak , Pavlos Protopapas , Sauro Succi

We developed a novel autonomously dynamic nonlocal turbulence model for the large and very large eddy simulation (LES, VLES) of the homogeneous isotropic turbulent flows (HIT). The model is based on a generalized (integer-to-noninteger)…

流体动力学 · 物理学 2022-03-07 S. Hadi Seyedi , Mohsen Zayernouri

Statistical properties of turbulent Rayleigh-Benard convection at low Prandtl numbers (Pr), which are typical for liquid metals such as mercury, gallium or liquid sodium, are investigated in high-resolution three-dimensional spectral…

流体动力学 · 物理学 2016-09-13 Janet D. Scheel , Joerg Schumacher

While direct numerical simulations (DNS) are the most accurate method for studying turbulence, their large computational cost restricts their use to idealized configurations and to Reynolds numbers well below those found in practical…

流体动力学 · 物理学 2025-12-09 Chang Hsin Chen , Arnab Moitro , Alexei Y. Poludnenko

Despite the increasing availability of high-performance computational resources, Reynolds-Averaged Navier-Stokes (RANS) simulations remain the workhorse for the analysis of turbulent flows in real-world applications. Linear eddy viscosity…

流体动力学 · 物理学 2023-11-27 Leon Riccius , Atul Agrawal , Phaedon-Stelios Koutsourelakis

A plane turbulent mixing in a shear flow of an ideal homogeneous fluid confined between two relatively close rigid walls is considered. The character of the flow is determined by interaction of vortices arising at the nonlinear stage of the…

流体动力学 · 物理学 2020-07-15 Alexander Chesnokov , Valery Liapidevskii

Boundary layer transition triggered by a discrete roughness element generates a turbulent wedge that spreads laterally as it proceeds downstream. Historical literature reports the spreading half angle is approximately 6$^{\circ}$ in…

流体动力学 · 物理学 2024-07-19 Alexandre R. Berger , Edward B. White

Reynolds-averaged Navier--Stokes (RANS) simulations with turbulence closure models continue to play important roles in industrial flow simulations. However, the commonly used linear eddy viscosity models are intrinsically unable to handle…

流体动力学 · 物理学 2019-05-22 Jin-Long Wu , Heng Xiao , Rui Sun , Qiqi Wang

This work introduces a novel data-driven framework to formulate explicit algebraic Reynolds-averaged Navier-Stokes (RANS) turbulence closures. Recent years have witnessed a blossom in applying machine learning (ML) methods to revolutionize…

流体动力学 · 物理学 2023-01-24 Hongwei Tang , Yan Wang , Tongguang Wang , Linlin Tian

Fundamental fluid--mechanics studies and many engineering developments are based on tripped cases. Therefore, it is essential for CFD simulations to replicate the same forced transition in spite of the availability of advanced transition…

流体动力学 · 物理学 2021-07-27 N. Tabatabaei , G. Fahland , A. Stroh , D. Gatti , B. Frohnapfel , M. Atzori , R. Vinuesa1 , P. Schlatter

We perform direct numerical simulation (DNS) and large eddy simulation (LES) of an initially spherical region of turbulence evolving in free space. The computations are performed with a lattice Green's function method, which allows the…

流体动力学 · 物理学 2021-04-22 Ke Yu , Tim Colonius , D. I. Pullin , Gregoire Winckelmans

Direct numerical simulation (DNS) of turbulent flows is computationally expensive and cannot be applied to flows with large Reynolds numbers. Large eddy simulation (LES) is an alternative that is computationally less demanding, but is…

流体动力学 · 物理学 2021-09-09 Shengyu Chen , Shervin Sammak , Peyman Givi , Joseph P. Yurko1 , Xiaowei Jia