Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters

Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotr...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Dorodnitsyn, L. V. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Synthetic turbulence Anisotropic turbulence Stochastic modeling Correlations of a random field

Anmerkung:	© Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Computational mathematics and modeling - Springer US, 1990, 34(2023), 2 vom: Apr., Seite 104-124
Übergeordnetes Werk:	volume:34 ; year:2023 ; number:2 ; month:04 ; pages:104-124

Links:	Volltext

DOI / URN:	10.1007/s10598-024-09601-z

Katalog-ID:	SPR057285233

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allfields	10.1007/s10598-024-09601-z doi (DE-627)SPR057285233 (SPR)s10598-024-09601-z-e DE-627 ger DE-627 rakwb eng 004 VZ 31.76 bkl 31.80 bkl Dorodnitsyn, L. V. verfasserin aut Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. Synthetic turbulence (dpeaa)DE-He213 Anisotropic turbulence (dpeaa)DE-He213 Stochastic modeling (dpeaa)DE-He213 Correlations of a random field (dpeaa)DE-He213 Enthalten in Computational mathematics and modeling Springer US, 1990 34(2023), 2 vom: Apr., Seite 104-124 (DE-627)325568634 (DE-600)2037135-4 1573-837X nnns volume:34 year:2023 number:2 month:04 pages:104-124 https://dx.doi.org/10.1007/s10598-024-09601-z X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.76 VZ 31.80 VZ AR 34 2023 2 04 104-124
spelling	10.1007/s10598-024-09601-z doi (DE-627)SPR057285233 (SPR)s10598-024-09601-z-e DE-627 ger DE-627 rakwb eng 004 VZ 31.76 bkl 31.80 bkl Dorodnitsyn, L. V. verfasserin aut Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. Synthetic turbulence (dpeaa)DE-He213 Anisotropic turbulence (dpeaa)DE-He213 Stochastic modeling (dpeaa)DE-He213 Correlations of a random field (dpeaa)DE-He213 Enthalten in Computational mathematics and modeling Springer US, 1990 34(2023), 2 vom: Apr., Seite 104-124 (DE-627)325568634 (DE-600)2037135-4 1573-837X nnns volume:34 year:2023 number:2 month:04 pages:104-124 https://dx.doi.org/10.1007/s10598-024-09601-z X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.76 VZ 31.80 VZ AR 34 2023 2 04 104-124
allfields_unstemmed	10.1007/s10598-024-09601-z doi (DE-627)SPR057285233 (SPR)s10598-024-09601-z-e DE-627 ger DE-627 rakwb eng 004 VZ 31.76 bkl 31.80 bkl Dorodnitsyn, L. V. verfasserin aut Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. Synthetic turbulence (dpeaa)DE-He213 Anisotropic turbulence (dpeaa)DE-He213 Stochastic modeling (dpeaa)DE-He213 Correlations of a random field (dpeaa)DE-He213 Enthalten in Computational mathematics and modeling Springer US, 1990 34(2023), 2 vom: Apr., Seite 104-124 (DE-627)325568634 (DE-600)2037135-4 1573-837X nnns volume:34 year:2023 number:2 month:04 pages:104-124 https://dx.doi.org/10.1007/s10598-024-09601-z X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.76 VZ 31.80 VZ AR 34 2023 2 04 104-124
allfieldsGer	10.1007/s10598-024-09601-z doi (DE-627)SPR057285233 (SPR)s10598-024-09601-z-e DE-627 ger DE-627 rakwb eng 004 VZ 31.76 bkl 31.80 bkl Dorodnitsyn, L. V. verfasserin aut Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. Synthetic turbulence (dpeaa)DE-He213 Anisotropic turbulence (dpeaa)DE-He213 Stochastic modeling (dpeaa)DE-He213 Correlations of a random field (dpeaa)DE-He213 Enthalten in Computational mathematics and modeling Springer US, 1990 34(2023), 2 vom: Apr., Seite 104-124 (DE-627)325568634 (DE-600)2037135-4 1573-837X nnns volume:34 year:2023 number:2 month:04 pages:104-124 https://dx.doi.org/10.1007/s10598-024-09601-z X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.76 VZ 31.80 VZ AR 34 2023 2 04 104-124
allfieldsSound	10.1007/s10598-024-09601-z doi (DE-627)SPR057285233 (SPR)s10598-024-09601-z-e DE-627 ger DE-627 rakwb eng 004 VZ 31.76 bkl 31.80 bkl Dorodnitsyn, L. V. verfasserin aut Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. Synthetic turbulence (dpeaa)DE-He213 Anisotropic turbulence (dpeaa)DE-He213 Stochastic modeling (dpeaa)DE-He213 Correlations of a random field (dpeaa)DE-He213 Enthalten in Computational mathematics and modeling Springer US, 1990 34(2023), 2 vom: Apr., Seite 104-124 (DE-627)325568634 (DE-600)2037135-4 1573-837X nnns volume:34 year:2023 number:2 month:04 pages:104-124 https://dx.doi.org/10.1007/s10598-024-09601-z X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.76 VZ 31.80 VZ AR 34 2023 2 04 104-124
language	English
source	Enthalten in Computational mathematics and modeling 34(2023), 2 vom: Apr., Seite 104-124 volume:34 year:2023 number:2 month:04 pages:104-124
sourceStr	Enthalten in Computational mathematics and modeling 34(2023), 2 vom: Apr., Seite 104-124 volume:34 year:2023 number:2 month:04 pages:104-124
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Synthetic turbulence Anisotropic turbulence Stochastic modeling Correlations of a random field
dewey-raw	004
isfreeaccess_bool	false
container_title	Computational mathematics and modeling
authorswithroles_txt_mv	Dorodnitsyn, L. V. @@aut@@
publishDateDaySort_date	2023-04-01T00:00:00Z
hierarchy_top_id	325568634
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language_de	englisch
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author	Dorodnitsyn, L. V.
spellingShingle	Dorodnitsyn, L. V. ddc 004 bkl 31.76 bkl 31.80 misc Synthetic turbulence misc Anisotropic turbulence misc Stochastic modeling misc Correlations of a random field Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters
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topic_title	004 VZ 31.76 bkl 31.80 bkl Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters Synthetic turbulence (dpeaa)DE-He213 Anisotropic turbulence (dpeaa)DE-He213 Stochastic modeling (dpeaa)DE-He213 Correlations of a random field (dpeaa)DE-He213
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title	Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters
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title_full	Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters
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title_sort	correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters
title_auth	Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters
abstract	Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. Adaptation of known methods of generation of a turbulent velocity field to the usage of a given tensor is demonstrated. © Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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title_short	Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters
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V.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The study is aimed at numerical modeling of turbulent flows, using an artificially generated random field. A multiparametric model of the spectral tensor of covariances of the stream function is proposed, reproducing the most important physical characteristics of a three-dimensional anisotropic turbulent field - incompressibility and quantitative values of Reynolds stresses and turbulence scales, obtained from a preliminary calculation. 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Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical p﻿arameters

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Correlation tensor of the stream function as the basis for modeling anisotropic turbulence with specified statistical parameters