Resolution-induced anisotropy in large-eddy simulations

Sigfried W. Haering, Myoungkyu Lee, and Robert D. Moser
Phys. Rev. Fluids 4, 114605 – Published 13 November 2019

Abstract

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 formulations. 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. Fluids 27, 085107 (2015)]. A simple model is presented here that is an anisotropic eddy diffusivity extension of the “Kolmogorov expression” eddy viscosity of Carati et al. [A family of dynamic models for large-eddy simulation, in Annual Research Briefs, Center for Turbulence Research (Stanford University and NASA AMES, 1995), pp. 35–40] 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.

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  • Received 15 April 2019

DOI:https://doi.org/10.1103/PhysRevFluids.4.114605

©2019 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
  1. Properties
Fluid Dynamics

Authors & Affiliations

Sigfried W. Haering* and Myoungkyu Lee2,†

  • The Oden Institute for Computational Engineering and Science, The University of Texas at Austin, Austin, Texas 78712, USA

Robert D. Moser

  • Department of Mechanical Engineering, The Oden Institute for Computational Engineering and Science, The University of Texas at Austin, Austin, Texas 78712, USA

  • *Present address: Argonne National Laboratory, Lemont, IL 60439, USA.
  • Present address: Sandia National Laboratories, Livermore, CA 94551, USA.

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Issue

Vol. 4, Iss. 11 — November 2019

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