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Journal of Scientific Computing

, Volume 79, Issue 2, pp 992–1014 | Cite as

Spectrally-Consistent Regularization of Navier–Stokes Equations

  • F. X. TriasEmail author
  • D. Folch
  • A. Gorobets
  • A. Oliva
Article

Abstract

The incompressible Navier–Stokes equations form an excellent mathematical model for turbulent flows. However, direct simulations at high Reynolds numbers are not feasible because the convective term produces far too many relevant scales of motion. Therefore, in the foreseeable future, numerical simulations of turbulent flows will have to resort to models of the small scales. Large-eddy simulation (LES) and regularization models are examples thereof. In the present work, we propose to combine both approaches in a spectrally-consistent way: i.e.  preserving the (skew-)symmetries of the differential operators. Restoring the Galilean invariance of the regularization method results into an additional hyperviscosity term. In this way, the convective production of small scales is effectively restrained whereas the destruction of the small scales is enhanced by this hyperviscosity effect. This approach leads to a blending between regularization of the convective term and LES. The performance of these improvements is assessed through application to Burgers’ equation, homogeneous isotropic turbulence and a turbulent channel flow.

Keywords

Regularization Navier–Stokes LES Turbulence 

Mathematics Subject Classification

76F65 76F05 76D05 

Notes

Acknowledgements

This work has been financially supported by the Ministerio de Economía y Competitividad, Spain (ENE2017-88697-R) and a Ramón y Cajal postdoctoral contract (RYC-2012-11996). Calculations have been performed on the IBM MareNostrum supercomputer at the Barcelona Supercomputing Center (FI-2016-3-0036). The authors thankfully acknowledge these institutions.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Heat and Mass Transfer Technological CenterTechnical University of Catalonia, ETSEIATTerrassaSpain
  2. 2.Keldysh Institute of Applied MathematicsMoscowRussia

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