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The effects of resolution and noise on kinematic features of fine-scale turbulence
The effect of spatial resolution and experimental noise on the kinematic fine-scale features in shear flow turbulence is investigated by means of comparing numerical and experimental data. A direct numerical simulation (DNS) of a nominally two-dimensional planar mixing layer is mean filtered onto a...
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Published in: | Experiments in fluids 2011-11, Vol.51 (5), p.1417-1437 |
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description | The effect of spatial resolution and experimental noise on the kinematic fine-scale features in shear flow turbulence is investigated by means of comparing numerical and experimental data. A direct numerical simulation (DNS) of a nominally two-dimensional planar mixing layer is mean filtered onto a uniform Cartesian grid at four different, progressively coarser, spatial resolutions. Spatial gradients are then calculated using a simple second-order scheme that is commonly used in experimental studies in order to make direct comparisons between the numerical and previously obtained experimental data. As expected, consistent with other studies, it is found that reduction of spatial resolution greatly reduces the frequency of high magnitude velocity gradients and thereby reduces the intermittency of the scalar analogues to strain (dissipation) and rotation (enstrophy). There is also an increase in the distances over which dissipation and enstrophy are spatially coherent in physical space as the resolution is coarsened, although these distances remain a constant number of grid points, suggesting that the data follow the applied filter. This reduction of intermittency is also observed in the eigenvalues of the strain-rate tensor as spatial resolution is reduced. The quantity with which these eigenvalues is normalised is shown to be extremely important as fine-scale quantities, such as the Kolmogorov length scale, are showed to change with different spatial resolution. This leads to a slight change in the modal values for these eigenvalues when normalised by the local Kolmogorov scale, which is not observed when they are normalised by large-scale, resolution-independent quantities. The interaction between strain and rotation is examined by means of the joint probability density function (
pdf
) between the second and third invariants of the characteristic equation of the velocity gradient tensor,
Q
and
R
respectively and by the alignments between the eigenvectors of the strain-rate tensor and the vorticity vector. Gaussian noise is shown to increase the divergence error of a dataset and subsequently affect both the
Q
–
R
joint
pdf
and the magnitude of the alignment cosines. The experimental datasets are showed to behave qualitatively similarly to the numerical datasets to which Gaussian noise has been added, confirming the importance of understanding the limitations of coarsely resolved, noisy experimental data. |
doi_str_mv | 10.1007/s00348-011-1159-2 |
format | article |
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pdf
) between the second and third invariants of the characteristic equation of the velocity gradient tensor,
Q
and
R
respectively and by the alignments between the eigenvectors of the strain-rate tensor and the vorticity vector. Gaussian noise is shown to increase the divergence error of a dataset and subsequently affect both the
Q
–
R
joint
pdf
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pdf
) between the second and third invariants of the characteristic equation of the velocity gradient tensor,
Q
and
R
respectively and by the alignments between the eigenvectors of the strain-rate tensor and the vorticity vector. Gaussian noise is shown to increase the divergence error of a dataset and subsequently affect both the
Q
–
R
joint
pdf
and the magnitude of the alignment cosines. The experimental datasets are showed to behave qualitatively similarly to the numerical datasets to which Gaussian noise has been added, confirming the importance of understanding the limitations of coarsely resolved, noisy experimental data.</description><subject>Eigenvalues</subject><subject>Engineering</subject><subject>Engineering Fluid Dynamics</subject><subject>Engineering Thermodynamics</subject><subject>Exact sciences and technology</subject><subject>Fluid dynamics</subject><subject>Fluid flow</subject><subject>Fluid- and Aerodynamics</subject><subject>Fundamental areas of phenomenology (including applications)</subject><subject>Heat and Mass Transfer</subject><subject>Instrumentation for fluid dynamics</subject><subject>Mathematical analysis</subject><subject>Noise</subject><subject>Physics</subject><subject>Probability density functions</subject><subject>Research Article</subject><subject>Spatial resolution</subject><subject>Tensors</subject><subject>Turbulence simulation and modeling</subject><subject>Turbulent flow</subject><subject>Turbulent flows, convection, and heat transfer</subject><issn>0723-4864</issn><issn>1432-1114</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LxDAQhoMouK7-AG-9CF6iySSbtkdZ_IIFQdZzSJOJdu2ma9Ie_Pem7OJRT2FmnrwzPIRccnbDGStvE2NCVpRxTjlf1BSOyIxLAbni8pjMWAmCykrJU3KW0oaxDLFqRl7XH1ig92iHVPS-iJj6bhzaPhQmuCL0bcIiF59twK0ZWlt4NMOYsYn2uUuTNR0WudeMHQaL5-TEmy7hxeGdk7eH-_Xyia5eHp-XdytqZS0GmteXzDoAyRqOta9r57hwxjhjFcICJQITvrbKNU2lSieMVK62XingJYCYk-t97i72XyOmQW_bZLHrTMB-TJorCVBWUIn_0QUHAVKqCeV71MY-pYhe72K7NfFbc6Yn1XqvWmfVelKtp0uuDvFmkuGjCbZNvx9BllCV9cTBnkt5FN4x6k0_xpAl_RH-A-8djck</recordid><startdate>20111101</startdate><enddate>20111101</enddate><creator>Buxton, O. R. H.</creator><creator>Laizet, S.</creator><creator>Ganapathisubramani, B.</creator><general>Springer-Verlag</general><general>Springer</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><scope>7TB</scope><scope>7U5</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20111101</creationdate><title>The effects of resolution and noise on kinematic features of fine-scale turbulence</title><author>Buxton, O. R. H. ; Laizet, S. ; Ganapathisubramani, B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c493t-90870cd2240b1e9f99dd13daadac6e25e4e203f9c6dbb867d3a46d9cf66217223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Eigenvalues</topic><topic>Engineering</topic><topic>Engineering Fluid Dynamics</topic><topic>Engineering Thermodynamics</topic><topic>Exact sciences and technology</topic><topic>Fluid dynamics</topic><topic>Fluid flow</topic><topic>Fluid- and Aerodynamics</topic><topic>Fundamental areas of phenomenology (including applications)</topic><topic>Heat and Mass Transfer</topic><topic>Instrumentation for fluid dynamics</topic><topic>Mathematical analysis</topic><topic>Noise</topic><topic>Physics</topic><topic>Probability density functions</topic><topic>Research Article</topic><topic>Spatial resolution</topic><topic>Tensors</topic><topic>Turbulence simulation and modeling</topic><topic>Turbulent flow</topic><topic>Turbulent flows, convection, and heat transfer</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Buxton, O. R. H.</creatorcontrib><creatorcontrib>Laizet, S.</creatorcontrib><creatorcontrib>Ganapathisubramani, B.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Experiments in fluids</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Buxton, O. R. H.</au><au>Laizet, S.</au><au>Ganapathisubramani, B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The effects of resolution and noise on kinematic features of fine-scale turbulence</atitle><jtitle>Experiments in fluids</jtitle><stitle>Exp Fluids</stitle><date>2011-11-01</date><risdate>2011</risdate><volume>51</volume><issue>5</issue><spage>1417</spage><epage>1437</epage><pages>1417-1437</pages><issn>0723-4864</issn><eissn>1432-1114</eissn><coden>EXFLDU</coden><abstract>The effect of spatial resolution and experimental noise on the kinematic fine-scale features in shear flow turbulence is investigated by means of comparing numerical and experimental data. A direct numerical simulation (DNS) of a nominally two-dimensional planar mixing layer is mean filtered onto a uniform Cartesian grid at four different, progressively coarser, spatial resolutions. Spatial gradients are then calculated using a simple second-order scheme that is commonly used in experimental studies in order to make direct comparisons between the numerical and previously obtained experimental data. As expected, consistent with other studies, it is found that reduction of spatial resolution greatly reduces the frequency of high magnitude velocity gradients and thereby reduces the intermittency of the scalar analogues to strain (dissipation) and rotation (enstrophy). There is also an increase in the distances over which dissipation and enstrophy are spatially coherent in physical space as the resolution is coarsened, although these distances remain a constant number of grid points, suggesting that the data follow the applied filter. This reduction of intermittency is also observed in the eigenvalues of the strain-rate tensor as spatial resolution is reduced. The quantity with which these eigenvalues is normalised is shown to be extremely important as fine-scale quantities, such as the Kolmogorov length scale, are showed to change with different spatial resolution. This leads to a slight change in the modal values for these eigenvalues when normalised by the local Kolmogorov scale, which is not observed when they are normalised by large-scale, resolution-independent quantities. The interaction between strain and rotation is examined by means of the joint probability density function (
pdf
) between the second and third invariants of the characteristic equation of the velocity gradient tensor,
Q
and
R
respectively and by the alignments between the eigenvectors of the strain-rate tensor and the vorticity vector. Gaussian noise is shown to increase the divergence error of a dataset and subsequently affect both the
Q
–
R
joint
pdf
and the magnitude of the alignment cosines. The experimental datasets are showed to behave qualitatively similarly to the numerical datasets to which Gaussian noise has been added, confirming the importance of understanding the limitations of coarsely resolved, noisy experimental data.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s00348-011-1159-2</doi><tpages>21</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Eigenvalues Engineering Engineering Fluid Dynamics Engineering Thermodynamics Exact sciences and technology Fluid dynamics Fluid flow Fluid- and Aerodynamics Fundamental areas of phenomenology (including applications) Heat and Mass Transfer Instrumentation for fluid dynamics Mathematical analysis Noise Physics Probability density functions Research Article Spatial resolution Tensors Turbulence simulation and modeling Turbulent flow Turbulent flows, convection, and heat transfer |
title | The effects of resolution and noise on kinematic features of fine-scale turbulence |
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