Wall-Modeled Large-Eddy Simulation for Complex Turbulent Flows

Bose, Sanjeeb; Park, George Ilhwan

doi:10.1146/annurev-fluid-122316-045241

Cited by 391 publications

(209 citation statements)

References 119 publications

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“…These friction losses are responsible for roughly 10% of the electric energy consumption worldwide (Kühnen et al 2018). Moreover, the success of large-eddy simulation (LES), which is an indispensable tool for scientific and engineering applications (Bose & Park 2018), lies in its ability to correctly reproduce energy transfer among scales. Hence, a comprehensive analysis of the interscale energy transfer mechanism is indispensable for both physical understanding of turbulence and for conducting high-fidelity LES.…”

Section: Introductionmentioning

confidence: 99%

The coherent structure of the kinetic energy transfer in shear turbulence

et al. 2020

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The cascade of energy in turbulent flows, i.e., the transfer of kinetic energy from large to small flow scales or vice versa (backward cascade), is the cornerstone of most theories and models of turbulence since the 1940s. Yet, understanding the spatial organisation of kinetic energy transfer remains an outstanding challenge in fluid mechanics. Here, we unveil the three-dimensional structure of the energy cascade across the shear-dominated scales using numerical data of homogeneous shear turbulence. We show that the characteristic flow structure associated with the energy transfer is a vortex shaped as an inverted hairpin followed by an upright hairpin. The asymmetry between the forward and backward cascade arises from the opposite flow circulation within the hairpins, which triggers reversed patterns in the flow.

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Section: Introductionmentioning

confidence: 99%

The coherent structure of the kinetic energy transfer in shear turbulence

et al. 2020

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“…An alternative method proposed here involves following the approach commonly used for wall modeling in finite differences . In this approach, the grid extends all the way to the solid wall (Figure B) and we are, in fact, imposing the wall shear stress at y =0, in terms of the velocity evaluated at y = d , where d now denotes the distance between the first grid point (B), which now coincides with the wall, and the first grid point off the wall (C).…”

Section: Wall Modelingmentioning

confidence: 99%

“…An alternative method proposed here involves following the approach commonly used for wall modeling in finite differences. [1][2][3][4][5] In this approach, the grid extends all the way to the solid wall ( Figure 1B) and we are, in fact, imposing the wall shear stress at y = 0, in terms of the velocity evaluated at y = d, where d now denotes the distance between the first grid point (B), which now coincides with the wall, and the first grid point off the wall (C). Due to the fact that this velocity has a nonzero vertical component, the problem outlined in the previous paragraph in regards to the resolved stress being zero at a distance y = d from the wall is solved.…”

Section: Classical Finite Difference Approachmentioning

confidence: 99%

“…They can be categorized into two groups, those that directly model the wall stress and those that employ a Reynolds-averaged Navier-Stokes (RANS) approach in the inner layer. The reader can refer (A) Finite element (B) Proposed approach FIGURE 1 Wall-modeling approach in different spatial discretization methods to other works [1][2][3][4][5] for additional information on the wall models. In this work, we focus on the implementation of wall modeling for LES in a finite element (FE) framework.…”

Section: Introductionmentioning

confidence: 99%

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Wall‐modeled large‐eddy simulation in a finite element framework

Owen

Chrysokentis

Ávila

et al. 2019

Numerical Methods in Fluids

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Summary This work studies the implementation of wall modeling for large‐eddy simulation in a finite element context. It provides a detailed description of how the approach used by the finite volume and finite differences communities is adapted to the finite element context. The new implementation is as simple and easy to implement as the classical finite element one, but it provides vastly superior results. In the typical approach used in finite elements, the mesh does not extend all the way to the wall, and the wall stress is evaluated at the first grid point, based on the velocity at the same point. Instead, we adopt the approach commonly used in finite differences, where the mesh covers the whole domain and the wall stress is obtained at the wall grid point, with the velocity evaluated at the first grid point off the wall. The method is tested in a turbulent channel flow at Reτ=2003, a neutral atmospheric boundary layer flow, and a flow over a wall‐mounted hump, with significant improvement in the results compared to the standard finite element approach. Additionally, we examine the effect of evaluating the input velocity further away from the wall, as well as applying temporal filtering on the wall‐model input.

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“…where D is the domain of resolved wavenumbers. The structure of G ijkl as given in (5) implies that it can be written in terms of a fourth-ranked tensor A ijkl , which is invariant to all permutations of its indices:…”

Section: Resolution-induced Anisotropiesmentioning

confidence: 99%

Resolution-induced anisotropy in large-eddy simulations

Haering

Lee²,

Moser

2019

Phys. Rev. Fluids

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Large eddy simulation (LES) of turbulence in complex geometries and domains is often conducted with high aspect ratio resolution cells of varying shapes and orientations. The effects of such anisotropic resolution are often simplified or neglected in subgrid model formulation. Here, we examine resolution induced anisotropy and demonstrate that, even for isotropic turbulence, anisotropic resolution induces mild resolved Reynolds stress anisotropy and significant anisotropy in second-order resolved velocity gradient statistics. In large eddy simulations of homogeneous isotropic turbulence with anisotropic resolution, it is shown that commonly used subgrid models, including those that consider resolution anisotropy in their formulation, perform poorly. The one exception is the anisotropic minimum dissipation model proposed by Rozema et al. (Phys. of Fluids 27, 085107, 2015). A simple new model is presented here that is formulated with an anisotropic eddy diffusivity that depends explicitly on the anisotropy of the resolution. It also performs well, and is remarkable because unlike other LES subgrid models, the eddy diffusivity only depends on statistical characteristics of the turbulence (in this case the dissipation rate), not on fluctuating quantities. In other subgrid modeling formulations, such as the dynamic procedure, limiting flow dependence to statistical quantities in this way could have advantages. arXiv:1812.03261v2 [physics.flu-dyn]

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Wall-Modeled Large-Eddy Simulation for Complex Turbulent Flows

Cited by 391 publications

References 119 publications

The coherent structure of the kinetic energy transfer in shear turbulence

The coherent structure of the kinetic energy transfer in shear turbulence

Wall‐modeled large‐eddy simulation in a finite element framework

Resolution-induced anisotropy in large-eddy simulations

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