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Anisotropic source modelling for turbulent jet noise prediction
An anisotropic component of the jet noise source model for the Reynolds-averaged Navier–Stokes equation-based jet noise prediction method is proposed. The modelling is based on Goldstein's generalized acoustic analogy, and both the fine-scale and large-scale turbulent noise sources are consider...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6801392/ https://www.ncbi.nlm.nih.gov/pubmed/31607245 http://dx.doi.org/10.1098/rsta.2019.0075 |
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author | Xu, Xihai Li, Xiaodong |
author_facet | Xu, Xihai Li, Xiaodong |
author_sort | Xu, Xihai |
collection | PubMed |
description | An anisotropic component of the jet noise source model for the Reynolds-averaged Navier–Stokes equation-based jet noise prediction method is proposed. The modelling is based on Goldstein's generalized acoustic analogy, and both the fine-scale and large-scale turbulent noise sources are considered. To model the anisotropic characteristics of jet noise source, the Reynolds stress tensor is used in place of the turbulent kinetic energy. The Launder–Reece–Rodi model (LRR), combined with Menter's ω-equation for the length scale, with modified coefficients developed by the present authors, is used to calculate the mean flow velocities and Reynolds stresses accurately. Comparison between predicted results and acoustic data has been carried out to verify the accuracy of the new anisotropic source model. This article is part of the theme issue ‘Frontiers of aeroacoustics research: theory, computation and experiment’. |
format | Online Article Text |
id | pubmed-6801392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-68013922019-10-21 Anisotropic source modelling for turbulent jet noise prediction Xu, Xihai Li, Xiaodong Philos Trans A Math Phys Eng Sci Articles An anisotropic component of the jet noise source model for the Reynolds-averaged Navier–Stokes equation-based jet noise prediction method is proposed. The modelling is based on Goldstein's generalized acoustic analogy, and both the fine-scale and large-scale turbulent noise sources are considered. To model the anisotropic characteristics of jet noise source, the Reynolds stress tensor is used in place of the turbulent kinetic energy. The Launder–Reece–Rodi model (LRR), combined with Menter's ω-equation for the length scale, with modified coefficients developed by the present authors, is used to calculate the mean flow velocities and Reynolds stresses accurately. Comparison between predicted results and acoustic data has been carried out to verify the accuracy of the new anisotropic source model. This article is part of the theme issue ‘Frontiers of aeroacoustics research: theory, computation and experiment’. The Royal Society Publishing 2019-12-02 2019-10-14 /pmc/articles/PMC6801392/ /pubmed/31607245 http://dx.doi.org/10.1098/rsta.2019.0075 Text en © 2019 The Authors. http://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/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles Xu, Xihai Li, Xiaodong Anisotropic source modelling for turbulent jet noise prediction |
title | Anisotropic source modelling for turbulent jet noise prediction |
title_full | Anisotropic source modelling for turbulent jet noise prediction |
title_fullStr | Anisotropic source modelling for turbulent jet noise prediction |
title_full_unstemmed | Anisotropic source modelling for turbulent jet noise prediction |
title_short | Anisotropic source modelling for turbulent jet noise prediction |
title_sort | anisotropic source modelling for turbulent jet noise prediction |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6801392/ https://www.ncbi.nlm.nih.gov/pubmed/31607245 http://dx.doi.org/10.1098/rsta.2019.0075 |
work_keys_str_mv | AT xuxihai anisotropicsourcemodellingforturbulentjetnoiseprediction AT lixiaodong anisotropicsourcemodellingforturbulentjetnoiseprediction |