Navier-stokes-alpha model: LES equations with nonlinear dispersion

File Description SizeFormat 
0103036v1.pdfWorking paper179.14 kBAdobe PDFView/Open
Title: Navier-stokes-alpha model: LES equations with nonlinear dispersion
Authors: Domaradzki, JA
Holm, DD
Item Type: Working Paper
Abstract: We present a framework for discussing LES equations with nonlinear dispersion. In this framework, we discuss the properties of the nonlinearly dispersive Navier-Stokes-alpha model of incompressible fluid turbulence --- also called the viscous Camassa-Holm equations and the LANS equations in the literature --- in comparison with the corresponding properties of large eddy simulation (LES) equations obtained via the approximate-inverse approach. In this comparison, we identify the spatially filtered NS-alpha equations with a class of generalized LES similarity models. Applying a certain approximate inverse to this class of LES models restores the Kelvin circulation theorem for the defiltered velocity and shows that the NS-alpha model describes the dynamics of the defiltered velocity for this class of generalized LES similarity models. We also show that the subgrid scale forces in the NS-alpha model transform covariantly under Galilean transformations and under a change to a uniformly rotating reference frame. Finally, we discuss in the spectral formulation how the NS-alpha model retains the local interactions among the large scales, retains the nonlocal sweeping effects of large scales on small scales, yet attenuates the local interactions of the small scales amongst themselves.
Issue Date: 23-Mar-2001
URI: http://hdl.handle.net/10044/1/72584
Publisher: arXiv
Copyright Statement: © 2001 The Authors.
Keywords: nlin.CD
nlin.CD
nlin.CD
nlin.CD
Notes: 15 pages, no figures, Special LES volume of ERCOFTAC bulletin, to appear in 2001
Publication Status: Published
Open Access location: https://arxiv.org/abs/nlin/0103036
Appears in Collections:Mathematics
Applied Mathematics and Mathematical Physics



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commons