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The local wavenumber model for computation of turbulent mixing

We present an overview of the current status in the development of a two-point spectral closure model for turbulent flows, known as the local wavenumber (LWN) model. The model is envisioned as a practical option for applications requiring multi-physics simulations in which statistical hydrodynamics...

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Detalles Bibliográficos
Autores principales: Kurien, Susan, Pal, Nairita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8802036/
https://www.ncbi.nlm.nih.gov/pubmed/35094556
http://dx.doi.org/10.1098/rsta.2021.0076
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author Kurien, Susan
Pal, Nairita
author_facet Kurien, Susan
Pal, Nairita
author_sort Kurien, Susan
collection PubMed
description We present an overview of the current status in the development of a two-point spectral closure model for turbulent flows, known as the local wavenumber (LWN) model. The model is envisioned as a practical option for applications requiring multi-physics simulations in which statistical hydrodynamics quantities such as Reynolds stresses, turbulent kinetic energy, and measures of mixing such as density-correlations and mix-width evolution, need to be captured with relatively high fidelity. In this review, we present the capabilities of the LWN model since it was first formulated in the early 1990s, for computations of increasing levels of complexity ranging from homogeneous isotropic turbulence, inhomogeneous and anisotropic single-fluid turbulence, to two-species mixing driven by buoyancy forces. The review concludes with a discussion of some of the more theoretical considerations that remain in the development of this model. This article is part of the theme issue ‘Scaling the turbulence edifice (part 2)’.
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spelling pubmed-88020362022-02-04 The local wavenumber model for computation of turbulent mixing Kurien, Susan Pal, Nairita Philos Trans A Math Phys Eng Sci Articles We present an overview of the current status in the development of a two-point spectral closure model for turbulent flows, known as the local wavenumber (LWN) model. The model is envisioned as a practical option for applications requiring multi-physics simulations in which statistical hydrodynamics quantities such as Reynolds stresses, turbulent kinetic energy, and measures of mixing such as density-correlations and mix-width evolution, need to be captured with relatively high fidelity. In this review, we present the capabilities of the LWN model since it was first formulated in the early 1990s, for computations of increasing levels of complexity ranging from homogeneous isotropic turbulence, inhomogeneous and anisotropic single-fluid turbulence, to two-species mixing driven by buoyancy forces. The review concludes with a discussion of some of the more theoretical considerations that remain in the development of this model. This article is part of the theme issue ‘Scaling the turbulence edifice (part 2)’. The Royal Society 2022-03-21 2022-01-31 /pmc/articles/PMC8802036/ /pubmed/35094556 http://dx.doi.org/10.1098/rsta.2021.0076 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Kurien, Susan
Pal, Nairita
The local wavenumber model for computation of turbulent mixing
title The local wavenumber model for computation of turbulent mixing
title_full The local wavenumber model for computation of turbulent mixing
title_fullStr The local wavenumber model for computation of turbulent mixing
title_full_unstemmed The local wavenumber model for computation of turbulent mixing
title_short The local wavenumber model for computation of turbulent mixing
title_sort local wavenumber model for computation of turbulent mixing
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8802036/
https://www.ncbi.nlm.nih.gov/pubmed/35094556
http://dx.doi.org/10.1098/rsta.2021.0076
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