On taylor correlation functions in isotropic turbulent flows
A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded as universal. Here, we show that Taylor correlations are analytically derived by hypothesizing turbulence as a phenomenon of superfluids at resonance...
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| Published in | Scientific reports Vol. 13; no. 1; pp. 3859 - 18 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
08.03.2023
Nature Publishing Group Nature Portfolio |
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| Abstract | A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded as universal. Here, we show that Taylor correlations are analytically derived by hypothesizing turbulence as a phenomenon of superfluids at resonance. Leveraging from a recent study on heat transfer at the speed of sound, we derived and fitted the longitudinal and lateral turbulent velocities in an isotropic, turbulent flow. The concept of the boundary of the second law helps to specify the integration constants in the solution. From the velocity profiles, Taylor’s correlation functions are analytically determined. From the linearity of the eigenfunction, we introduce amplitude and frequency factors. These factors are curve-fitted with two experimental dataset. Additional experimental datasets in the public domain are compared to the correlations, which shows that the theory agrees with experiments very well in isotropic flows. The analytical correlation functions help to elucidate observations that experiments and statistical mechanics have challenges to explain. |
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| AbstractList | A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded as universal. Here, we show that Taylor correlations are analytically derived by hypothesizing turbulence as a phenomenon of superfluids at resonance. Leveraging from a recent study on heat transfer at the speed of sound, we derived and fitted the longitudinal and lateral turbulent velocities in an isotropic, turbulent flow. The concept of the boundary of the second law helps to specify the integration constants in the solution. From the velocity profiles, Taylor's correlation functions are analytically determined. From the linearity of the eigenfunction, we introduce amplitude and frequency factors. These factors are curve-fitted with two experimental dataset. Additional experimental datasets in the public domain are compared to the correlations, which shows that the theory agrees with experiments very well in isotropic flows. The analytical correlation functions help to elucidate observations that experiments and statistical mechanics have challenges to explain. A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded as universal. Here, we show that Taylor correlations are analytically derived by hypothesizing turbulence as a phenomenon of superfluids at resonance. Leveraging from a recent study on heat transfer at the speed of sound, we derived and fitted the longitudinal and lateral turbulent velocities in an isotropic, turbulent flow. The concept of the boundary of the second law helps to specify the integration constants in the solution. From the velocity profiles, Taylor's correlation functions are analytically determined. From the linearity of the eigenfunction, we introduce amplitude and frequency factors. These factors are curve-fitted with two experimental dataset. Additional experimental datasets in the public domain are compared to the correlations, which shows that the theory agrees with experiments very well in isotropic flows. The analytical correlation functions help to elucidate observations that experiments and statistical mechanics have challenges to explain.A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded as universal. Here, we show that Taylor correlations are analytically derived by hypothesizing turbulence as a phenomenon of superfluids at resonance. Leveraging from a recent study on heat transfer at the speed of sound, we derived and fitted the longitudinal and lateral turbulent velocities in an isotropic, turbulent flow. The concept of the boundary of the second law helps to specify the integration constants in the solution. From the velocity profiles, Taylor's correlation functions are analytically determined. From the linearity of the eigenfunction, we introduce amplitude and frequency factors. These factors are curve-fitted with two experimental dataset. Additional experimental datasets in the public domain are compared to the correlations, which shows that the theory agrees with experiments very well in isotropic flows. The analytical correlation functions help to elucidate observations that experiments and statistical mechanics have challenges to explain. Abstract A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded as universal. Here, we show that Taylor correlations are analytically derived by hypothesizing turbulence as a phenomenon of superfluids at resonance. Leveraging from a recent study on heat transfer at the speed of sound, we derived and fitted the longitudinal and lateral turbulent velocities in an isotropic, turbulent flow. The concept of the boundary of the second law helps to specify the integration constants in the solution. From the velocity profiles, Taylor’s correlation functions are analytically determined. From the linearity of the eigenfunction, we introduce amplitude and frequency factors. These factors are curve-fitted with two experimental dataset. Additional experimental datasets in the public domain are compared to the correlations, which shows that the theory agrees with experiments very well in isotropic flows. The analytical correlation functions help to elucidate observations that experiments and statistical mechanics have challenges to explain. |
| ArticleNumber | 3859 |
| Author | Chen, Wei |
| Author_xml | – sequence: 1 givenname: Wei surname: Chen fullname: Chen, Wei email: askelf123@yahoo.com organization: Department of Applied Mathematics, University of Science and Technology Beijing, General Electric |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36890177$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1017/CBO9780511810763 10.1017/CBO9780511840531 10.1017/CBO9781139170666 10.1017/S0022112071001599 10.1063/1.1761199 10.1103/PhysRevA.23.2673 10.1098/rspa.1936.0214 10.1098/rspa.1938.0032 10.1098/rspa.1954.0049 10.1016/j.physrep.2004.07.007 10.1090/qam/11999 10.1017/CBO9780511919701 10.1103/PhysRevB.95.094518 10.1016/j.ijheatmasstransfer.2021.121529 10.1007/BF00401584 |
| ContentType | Journal Article |
| Copyright | The Author(s) 2023 2023. The Author(s). The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Snippet | A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded as... Abstract A turbulent flow can be characterized by Taylor correlation functions which are obtained empirically, understood by statistical mechanics and regarded... |
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| SubjectTerms | 639/166/984 639/766/25 Heat transfer Humanities and Social Sciences multidisciplinary Science Science (multidisciplinary) Statistical mechanics Statistics Turbulent flow |
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| Title | On taylor correlation functions in isotropic turbulent flows |
| URI | https://link.springer.com/article/10.1038/s41598-023-30825-3 https://www.ncbi.nlm.nih.gov/pubmed/36890177 https://www.proquest.com/docview/2784721534 https://www.proquest.com/docview/2785200561 https://pubmed.ncbi.nlm.nih.gov/PMC9995477 https://doaj.org/article/753ae4a25f5b4225b81832ae31be8e89 |
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