Architecture of Approximate Deconvolution Models of Turbulence

A. Labovschii; W. Layton; C. Manica; M. Neda; L. Rebholz; Iuliana Stanculescu; C. Trenchea

Architecture of Approximate Deconvolution Models of Turbulence

A. Labovschii
, W. Layton
, C. Manica
, M. Neda
, L. Rebholz
, Iuliana Stanculescu
, C. Trenchea

Department of Mathematics

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This report presents the mathematical foundation of approximate deconvolution LES models together with the model phenomenology downstream of the theory. This mathematical foundation now begins to be complete for the incompressible Navier–Stokes equations. It is built upon averaging, deconvolving and addressing closure so as to obtain the physically correct energy and helicity balances in the LES model. We show how this is determined and how correct energy balance implies correct prediction of turbulent statistics. Interestingly, the approach is simple and thus gives a road map to develop models for more complex turbulent flows. We illustrate this herein for the case of MHD turbulence.

Original language	American English
Title of host publication	Quality and Reliability of Large-Eddy Simulations
Editors	Johan Meyers, Bernard J. Geurts, Pierre Sagaut
Pages	3-20
Number of pages	18
State	Published - Jan 1 2008

Publication series

Name	ERCOFTAC Series
Volume	12

Bibliographical note

Publisher Copyright:
© Springer Science+Business Media B.V. 2008.

Funding

This work was partially supported by NSF Grant DMS 0508260

Funders	Funder number
National Sleep Foundation	DMS 0508260

ASJC Scopus Subject Areas

Fluid Flow and Transfer Processes
Computational Mathematics

Keywords

Deconvolution
Energy cascade
Helicity
MHD

Disciplines

Mathematics

Cite this

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title = "Architecture of Approximate Deconvolution Models of Turbulence",

abstract = " This report presents the mathematical foundation of approximate deconvolution LES models together with the model phenomenology downstream of the theory. This mathematical foundation now begins to be complete for the incompressible Navier–Stokes equations. It is built upon averaging, deconvolving and addressing closure so as to obtain the physically correct energy and helicity balances in the LES model. We show how this is determined and how correct energy balance implies correct prediction of turbulent statistics. Interestingly, the approach is simple and thus gives a road map to develop models for more complex turbulent flows. We illustrate this herein for the case of MHD turbulence.",

keywords = "Deconvolution, Energy cascade, Helicity, MHD",

author = "A. Labovschii and W. Layton and C. Manica and M. Neda and L. Rebholz and Iuliana Stanculescu and C. Trenchea",

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language = "American English",

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TY - CHAP

T1 - Architecture of Approximate Deconvolution Models of Turbulence

AU - Labovschii, A.

AU - Layton, W.

AU - Manica, C.

AU - Neda, M.

AU - Rebholz, L.

AU - Stanculescu, Iuliana

AU - Trenchea, C.

PY - 2008/1/1

Y1 - 2008/1/1

N2 - This report presents the mathematical foundation of approximate deconvolution LES models together with the model phenomenology downstream of the theory. This mathematical foundation now begins to be complete for the incompressible Navier–Stokes equations. It is built upon averaging, deconvolving and addressing closure so as to obtain the physically correct energy and helicity balances in the LES model. We show how this is determined and how correct energy balance implies correct prediction of turbulent statistics. Interestingly, the approach is simple and thus gives a road map to develop models for more complex turbulent flows. We illustrate this herein for the case of MHD turbulence.

AB - This report presents the mathematical foundation of approximate deconvolution LES models together with the model phenomenology downstream of the theory. This mathematical foundation now begins to be complete for the incompressible Navier–Stokes equations. It is built upon averaging, deconvolving and addressing closure so as to obtain the physically correct energy and helicity balances in the LES model. We show how this is determined and how correct energy balance implies correct prediction of turbulent statistics. Interestingly, the approach is simple and thus gives a road map to develop models for more complex turbulent flows. We illustrate this herein for the case of MHD turbulence.

KW - Deconvolution

KW - Energy cascade

KW - Helicity

KW - MHD

UR - https://nsuworks.nova.edu/cnso_math_facbooks/11

UR - https://www.scopus.com/pages/publications/84964882639

UR - https://www.scopus.com/pages/publications/84964882639#tab=citedBy

M3 - Chapter

SN - 9781402085772

T3 - ERCOFTAC Series

SP - 3

EP - 20

BT - Quality and Reliability of Large-Eddy Simulations

A2 - Meyers, Johan

A2 - Geurts, Bernard J.

A2 - Sagaut, Pierre

ER -

Architecture of Approximate Deconvolution Models of Turbulence

Abstract

Publication series

Bibliographical note

Funding

ASJC Scopus Subject Areas

Keywords

Disciplines

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