The multi-scale geometry of the near field in an axisymmetric jet
A characteristic feature of axisymmetric jets, and turbulent shear flows in general, is the entrainment of mass across the turbulent/non-turbulent interface (TNTI). The multi-scale nature of the TNTI surface area was recently observed to exhibit power-law scaling with a fractal dimension, $D_{f}$ ,...
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Veröffentlicht in: | Journal of fluid mechanics 2018-03, Vol.838, p.501-515 |
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description | A characteristic feature of axisymmetric jets, and turbulent shear flows in general, is the entrainment of mass across the turbulent/non-turbulent interface (TNTI). The multi-scale nature of the TNTI surface area was recently observed to exhibit power-law scaling with a fractal dimension,
$D_{f}$
, between
$D_{f}=2.3{-}2.4$
, inferred from two-dimensional data, in both high Reynolds number boundary layers and the far field of axisymmetric jets. In this paper, we show that the fractal scaling previously observed in the far field of an axisymmetric jet is established at the end of the potential core. Simultaneous measurements of the velocity and scalar fields were obtained and coarse grain filtering was applied over two decades of scale separation, showing that
$D_{f}$
evolves to
${\approx}2.35$
at
$x/d=4.6$
, which is similar to
$D_{f}$
found in the far field between
$x/d=40{-}60$
. This is evidence that scale separation becomes sufficiently developed to achieve scale invariance of the TNTI surface area in the near field of the jet well before self-similarity is established. We also observe that the onset of this geometric scale invariance coincides with the onset of radial homogeneity shown by two-point velocity correlations. Finally, we present a simple theoretical basis for these results using an exact fractal construction based on the Koch curve and applying a coarse-grain filtering analysis. |
doi_str_mv | 10.1017/jfm.2017.899 |
format | Article |
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$D_{f}$
, between
$D_{f}=2.3{-}2.4$
, inferred from two-dimensional data, in both high Reynolds number boundary layers and the far field of axisymmetric jets. In this paper, we show that the fractal scaling previously observed in the far field of an axisymmetric jet is established at the end of the potential core. Simultaneous measurements of the velocity and scalar fields were obtained and coarse grain filtering was applied over two decades of scale separation, showing that
$D_{f}$
evolves to
${\approx}2.35$
at
$x/d=4.6$
, which is similar to
$D_{f}$
found in the far field between
$x/d=40{-}60$
. This is evidence that scale separation becomes sufficiently developed to achieve scale invariance of the TNTI surface area in the near field of the jet well before self-similarity is established. We also observe that the onset of this geometric scale invariance coincides with the onset of radial homogeneity shown by two-point velocity correlations. Finally, we present a simple theoretical basis for these results using an exact fractal construction based on the Koch curve and applying a coarse-grain filtering analysis.</description><identifier>ISSN: 0022-1120</identifier><identifier>EISSN: 1469-7645</identifier><identifier>DOI: 10.1017/jfm.2017.899</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Boundary layers ; Computational fluid dynamics ; Entrainment ; Filtration ; Fluid flow ; Fluids ; Fractals ; Geometry ; Grain ; High Reynolds number ; Invariance ; JFM Papers ; Research methodology ; Reynolds number ; Scale invariance ; Scaling ; Self-similarity ; Separation ; Surface area ; Velocity</subject><ispartof>Journal of fluid mechanics, 2018-03, Vol.838, p.501-515</ispartof><rights>2018 Cambridge University Press</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c302t-703710dfd77021fa26f294f8a5e6ba4673b66e57af385a36f43e9bf313c3ae813</citedby><cites>FETCH-LOGICAL-c302t-703710dfd77021fa26f294f8a5e6ba4673b66e57af385a36f43e9bf313c3ae813</cites><orcidid>0000-0002-9150-5770</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S0022112017008990/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,776,780,27901,27902,55603</link.rule.ids></links><search><creatorcontrib>Mistry, Dhiren</creatorcontrib><creatorcontrib>Dawson, James R.</creatorcontrib><creatorcontrib>Kerstein, Alan R.</creatorcontrib><title>The multi-scale geometry of the near field in an axisymmetric jet</title><title>Journal of fluid mechanics</title><addtitle>J. Fluid Mech</addtitle><description>A characteristic feature of axisymmetric jets, and turbulent shear flows in general, is the entrainment of mass across the turbulent/non-turbulent interface (TNTI). The multi-scale nature of the TNTI surface area was recently observed to exhibit power-law scaling with a fractal dimension,
$D_{f}$
, between
$D_{f}=2.3{-}2.4$
, inferred from two-dimensional data, in both high Reynolds number boundary layers and the far field of axisymmetric jets. In this paper, we show that the fractal scaling previously observed in the far field of an axisymmetric jet is established at the end of the potential core. Simultaneous measurements of the velocity and scalar fields were obtained and coarse grain filtering was applied over two decades of scale separation, showing that
$D_{f}$
evolves to
${\approx}2.35$
at
$x/d=4.6$
, which is similar to
$D_{f}$
found in the far field between
$x/d=40{-}60$
. This is evidence that scale separation becomes sufficiently developed to achieve scale invariance of the TNTI surface area in the near field of the jet well before self-similarity is established. We also observe that the onset of this geometric scale invariance coincides with the onset of radial homogeneity shown by two-point velocity correlations. Finally, we present a simple theoretical basis for these results using an exact fractal construction based on the Koch curve and applying a coarse-grain filtering analysis.</description><subject>Boundary layers</subject><subject>Computational fluid dynamics</subject><subject>Entrainment</subject><subject>Filtration</subject><subject>Fluid flow</subject><subject>Fluids</subject><subject>Fractals</subject><subject>Geometry</subject><subject>Grain</subject><subject>High Reynolds number</subject><subject>Invariance</subject><subject>JFM Papers</subject><subject>Research methodology</subject><subject>Reynolds number</subject><subject>Scale invariance</subject><subject>Scaling</subject><subject>Self-similarity</subject><subject>Separation</subject><subject>Surface area</subject><subject>Velocity</subject><issn>0022-1120</issn><issn>1469-7645</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkE1rwzAMhs3YYF23236AYdclk-3ETo6l7AsKu3Rn4yRy55CPzk5h_fdzaGGXgUACPa8EDyH3DFIGTD21tk95HNKiLC_IgmWyTJTM8kuyAOA8YYzDNbkJoQVgAkq1IKvtF9L-0E0uCbXpkO5w7HHyRzpaOsXdgMZT67BrqBuoifXjwrGfGVfTFqdbcmVNF_Du3Jfk8-V5u35LNh-v7-vVJqkF8ClRIBSDxjZKAWfWcGl5mdnC5Cgrk0klKikxV8aKIjdC2kxgWVnBRC0MFkwsycPp7t6P3wcMk27Hgx_iS80hZgpQSkTq8UTVfgzBo9V773rjj5qBniXpKEnPknSUFPH0jJu-8q7Z4d_VfwO_CwxoJw</recordid><startdate>20180310</startdate><enddate>20180310</enddate><creator>Mistry, Dhiren</creator><creator>Dawson, James R.</creator><creator>Kerstein, Alan R.</creator><general>Cambridge University Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TB</scope><scope>7U5</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>L7M</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope><orcidid>https://orcid.org/0000-0002-9150-5770</orcidid></search><sort><creationdate>20180310</creationdate><title>The multi-scale geometry of the near field in an axisymmetric jet</title><author>Mistry, Dhiren ; Dawson, James R. ; Kerstein, Alan R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c302t-703710dfd77021fa26f294f8a5e6ba4673b66e57af385a36f43e9bf313c3ae813</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Boundary layers</topic><topic>Computational fluid dynamics</topic><topic>Entrainment</topic><topic>Filtration</topic><topic>Fluid flow</topic><topic>Fluids</topic><topic>Fractals</topic><topic>Geometry</topic><topic>Grain</topic><topic>High Reynolds number</topic><topic>Invariance</topic><topic>JFM Papers</topic><topic>Research methodology</topic><topic>Reynolds number</topic><topic>Scale invariance</topic><topic>Scaling</topic><topic>Self-similarity</topic><topic>Separation</topic><topic>Surface area</topic><topic>Velocity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mistry, Dhiren</creatorcontrib><creatorcontrib>Dawson, James R.</creatorcontrib><creatorcontrib>Kerstein, Alan R.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>Natural Science Collection (ProQuest)</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><jtitle>Journal of fluid mechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mistry, Dhiren</au><au>Dawson, James R.</au><au>Kerstein, Alan R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The multi-scale geometry of the near field in an axisymmetric jet</atitle><jtitle>Journal of fluid mechanics</jtitle><addtitle>J. Fluid Mech</addtitle><date>2018-03-10</date><risdate>2018</risdate><volume>838</volume><spage>501</spage><epage>515</epage><pages>501-515</pages><issn>0022-1120</issn><eissn>1469-7645</eissn><abstract>A characteristic feature of axisymmetric jets, and turbulent shear flows in general, is the entrainment of mass across the turbulent/non-turbulent interface (TNTI). The multi-scale nature of the TNTI surface area was recently observed to exhibit power-law scaling with a fractal dimension,
$D_{f}$
, between
$D_{f}=2.3{-}2.4$
, inferred from two-dimensional data, in both high Reynolds number boundary layers and the far field of axisymmetric jets. In this paper, we show that the fractal scaling previously observed in the far field of an axisymmetric jet is established at the end of the potential core. Simultaneous measurements of the velocity and scalar fields were obtained and coarse grain filtering was applied over two decades of scale separation, showing that
$D_{f}$
evolves to
${\approx}2.35$
at
$x/d=4.6$
, which is similar to
$D_{f}$
found in the far field between
$x/d=40{-}60$
. This is evidence that scale separation becomes sufficiently developed to achieve scale invariance of the TNTI surface area in the near field of the jet well before self-similarity is established. We also observe that the onset of this geometric scale invariance coincides with the onset of radial homogeneity shown by two-point velocity correlations. Finally, we present a simple theoretical basis for these results using an exact fractal construction based on the Koch curve and applying a coarse-grain filtering analysis.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/jfm.2017.899</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-9150-5770</orcidid></addata></record> |
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subjects | Boundary layers Computational fluid dynamics Entrainment Filtration Fluid flow Fluids Fractals Geometry Grain High Reynolds number Invariance JFM Papers Research methodology Reynolds number Scale invariance Scaling Self-similarity Separation Surface area Velocity |
title | The multi-scale geometry of the near field in an axisymmetric jet |
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