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Using vortex identifiers to build eddy-viscosity subgrid-scale models for large-eddy simulation

Xingjun Fang1,*, Bing-Chen Wang1, and Donald J. Bergstrom2

  • 1Department of Mechanical Engineering, University of Manitoba, Winnipeg, Canada MB R3T 5V6
  • 2Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada SK S7N 5A9

  • *fangx@myumanitoba.ca
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Phys. Rev. Fluids 4, 034606 – Published 26 March, 2019

DOI: https://doi.org/10.1103/PhysRevFluids.4.034606

Abstract

In this paper, we present a generalized framework of incorporating vortex identifiers into subgrid-scale (SGS) models for large-eddy simulation. This research is inspired by the keystone principle of modern turbulence theory that kinetic energy is cascaded from large to small scales by the vortex stretching mechanism. We propose that regions without local vortex structures do not possess significant subgrid motions due to the lack of energy cascade and therefore do not need significant SGS stresses/dissipation, whereas strong local SGS dissipation should be applied in regions with strong small-scale (close to the cutoff length scale) vortices owing to the subgrid motions enhanced by the vortex stretching mechanism. Following this idea, four new SGS models are constructed based on four different vortex identifiers. The new models possess some important characteristics of the vortex identifiers, including sensitivity to small-scale vortices and Galilean invariance. The correct near-wall cubic asymptotic behavior for the SGS viscosity is also satisfied by the new models. The proposed models are validated using three test cases, including isotropic decaying turbulence, isotropic forced turbulence, and fully developed turbulent channel flow. The proposed models are robust without any local clipping/filtering or averaging along homogeneous direction(s). The results indicate that the proposed models automatically apply stronger SGS dissipation to small-scale motions, and predict satisfactory turbulence statistics with less computational expense compared with the conventional dynamical Smagorinsky model.

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Phys. Rev. Fluids 4, 034606– Published 26 March, 2019
  • Received 14 August 2018
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