Published August 2015 | Version Published
Journal Article Open

Minimum-dissipation models for large-eddy simulation

  • 1. ROR icon University of Groningen
  • 2. ROR icon National Aerospace Laboratory
  • 3. ROR icon Stanford University

Abstract

Minimum-dissipation eddy-viscosity models are a class of sub-filter models for large-eddy simulation that give the minimum eddy dissipation required to dissipate the energy of sub-filter scales. A previously derived minimum-dissipation model is the QR model. This model is based on the invariants of the resolved rate-of-strain tensor and has many desirable properties. It appropriately switches off for laminar and transitional flows, has low computational complexity, and is consistent with the exact sub-filter tensor on isotropic grids. However, the QR model proposed in the literature gives insufficient eddy dissipation. It is demonstrated that this can be corrected by increasing the model constant. The corrected QR model gives good results in simulations of decaying grid turbulence on an isotropic grid. On anisotropic grids the QR model is not consistent with the exact sub-filter tensor and requires an approximation of the filter width. It is demonstrated that the results of the QR model on anisotropic grids are primarily determined by the used filter width approximation, and that no approximation gives satisfactory results in simulations of both a temporal mixing layer and turbulent channel flow. A new minimum-dissipation model for anisotropic grids is proposed. This anisotropic minimum-dissipation (AMD) model generalizes the desirable practical and theoretical properties of the QR model to anisotropic grids and does not require an approximation of the filter width. The AMD model is successfully applied in simulations of decaying grid turbulence on an isotropic grid and in simulations of a temporal mixing layer and turbulent channel flow on anisotropic grids.

Additional Information

© 2015 AIP Publishing LLC. Received 30 April 2015; accepted 5 August 2015; published online 19 August 2015. A part of this research was conducted at the Stanford CTR summer program 2014. W.R. and R.V. are grateful for the opportunity to participate in this program, the received financial support, and the interactions with the CTR staff and the participants of the summer program. W.R. receives financial support from the Ubbo Emmius Fund of the University of Groningen and kindly acknowledges support from the National Aerospace Laboratory NLR. W.R. and R.V. acknowledge sponsoring by the Netherlands Organization for Scientific Research (NWO) for the use of supercomputing facilities. H.J.B. receives financial support from the Stanford Graduate Fellowship.

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Identifiers

Eprint ID
108441
Resolver ID
CaltechAUTHORS:20210315-152246966

Funding

Stanford University
University of Groningen
National Aerospace Laboratory
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)

Dates

Created
2021-03-19
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Updated
2021-03-19
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