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The Stretched-Vortex SGS Model in Physical Space

Voelkl, T. and Pullin, D. I. and Henderson, R. D. (1999) The Stretched-Vortex SGS Model in Physical Space. In: Recent Advances in DNS and LES. Springer , Dordrecht, pp. 459-464. ISBN 978-94-010-5924-4. https://resolver.caltech.edu/CaltechAUTHORS:20200714-123705635

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Abstract

The stretched-vortex subgrid stress model for the large-eddy simulation of turbulent flows has been developed to the stage where it can be applied to realistic flow at large Reynolds numbers [1] [2]. The basic assumption of this model [3] is that the subgrid vortex structure consists of straight, stretched vortices containing a nearly axisymmetric subgrid vorticity field. Vortices of this type, such as the Burgers vortex and the stretched-spiral vortex have provided fair quantitative estimates of turbulence fine-scale properties [4]. These structures are probably an oversimplified model of fine-scale turbulence, but may nevertheless contain sufficient of the vortex-stretching and energy cascade physics characteristic of the small scales to provide a reasonable basis for subgrid-stress modelling for LES. The resulting subgrid stresses are Τ_(ij)=K(δ_(ij)−e^v_ie^v_j). (1) where K is the subgrid energy and e_i^ v , i = 1, 2, 3 are the direction cosines of the subgrid vortex axis. The local subgrid dissipation ϵ_(sgs) is equal to the product of K with the component of S_(ij) aligned with the vortex axis. A class of simple models is obtained when it is assumed that the subgrid vortices are aligned with the eigenvectors of the rate-of-strain tensor S_(ij) [1]. Utilizing an assumed Kolmogorov form for the local subgrid energy spectrum, the model estimates the turbulent energy production at the resolved-scale cutoff in terms of the model parameters ϵ and the Kolmogorov prefactor K₀ and adjusts these parameters locally so as to continue the cascade through the cutoff to the subgrid vortex structures where the dissipation takes place.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-94-011-4513-8_39DOIArticle
https://rdcu.be/b5B5NPublisherFree ReadCube access
Additional Information:© 1999 Springer Science+Business Media Dordrecht. This work was supported partially by the National Science Foundation under Grant CTS-9634222 and partially by the Academic Strategic Alliances Program of the Accelerated Strategic Computing Initiative (ASCII ASAP) under subcontract no. B341492 of DOE contract W-7405-ENG-48.
Group:GALCIT
Funders:
Funding AgencyGrant Number
NSFCTS-9634222
Department of Energy (DOE)B341492
Department of Energy (DOE)W-7405-ENG-48
DOI:10.1007/978-94-011-4513-8_39
Record Number:CaltechAUTHORS:20200714-123705635
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200714-123705635
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104382
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Jul 2020 19:52
Last Modified:16 Nov 2021 18:31

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