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On the transport equation for probability density functions of turbulent vorticity fields

Vorticity random fields of turbulent flows (modelled over the vorticity equation with random initial data for example) are singled out as the main dynamic variables for the description of turbulence, and the evolution equation of the probability density function (PDF) of the vorticity field has been...

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Detalles Bibliográficos
Autores principales: Li, Jiawei, Qian, Zhongmin, Zhou, Mingrui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8791048/
https://www.ncbi.nlm.nih.gov/pubmed/35153610
http://dx.doi.org/10.1098/rspa.2021.0534
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author Li, Jiawei
Qian, Zhongmin
Zhou, Mingrui
author_facet Li, Jiawei
Qian, Zhongmin
Zhou, Mingrui
author_sort Li, Jiawei
collection PubMed
description Vorticity random fields of turbulent flows (modelled over the vorticity equation with random initial data for example) are singled out as the main dynamic variables for the description of turbulence, and the evolution equation of the probability density function (PDF) of the vorticity field has been obtained. This PDF evolution equation is a mixed type partial differential equation (PDE) of second order which depends only on the conditional mean (which is a first-order statistics) of the underlying turbulent flow. This is in contrast with Reynolds mean flow equation which relies on a quadratic statistics. The PDF PDE may provide new closure schemes based on the first-order conditional statistics, and some of them will be described in the paper. We should mention that the PDF equation is interesting by its own and is worthy of study as a PDE of second order.
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spelling pubmed-87910482022-02-11 On the transport equation for probability density functions of turbulent vorticity fields Li, Jiawei Qian, Zhongmin Zhou, Mingrui Proc Math Phys Eng Sci Research Articles Vorticity random fields of turbulent flows (modelled over the vorticity equation with random initial data for example) are singled out as the main dynamic variables for the description of turbulence, and the evolution equation of the probability density function (PDF) of the vorticity field has been obtained. This PDF evolution equation is a mixed type partial differential equation (PDE) of second order which depends only on the conditional mean (which is a first-order statistics) of the underlying turbulent flow. This is in contrast with Reynolds mean flow equation which relies on a quadratic statistics. The PDF PDE may provide new closure schemes based on the first-order conditional statistics, and some of them will be described in the paper. We should mention that the PDF equation is interesting by its own and is worthy of study as a PDE of second order. The Royal Society 2022-01 2022-01-26 /pmc/articles/PMC8791048/ /pubmed/35153610 http://dx.doi.org/10.1098/rspa.2021.0534 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 Research Articles
Li, Jiawei
Qian, Zhongmin
Zhou, Mingrui
On the transport equation for probability density functions of turbulent vorticity fields
title On the transport equation for probability density functions of turbulent vorticity fields
title_full On the transport equation for probability density functions of turbulent vorticity fields
title_fullStr On the transport equation for probability density functions of turbulent vorticity fields
title_full_unstemmed On the transport equation for probability density functions of turbulent vorticity fields
title_short On the transport equation for probability density functions of turbulent vorticity fields
title_sort on the transport equation for probability density functions of turbulent vorticity fields
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8791048/
https://www.ncbi.nlm.nih.gov/pubmed/35153610
http://dx.doi.org/10.1098/rspa.2021.0534
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