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High-order generalisation of the diagnostic scaling for turbulent boundary layers
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0002-1663-3553
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0001-8667-0520
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0002-1146-3241
2016 (English)In: Journal of turbulence, ISSN 1468-5248, E-ISSN 1468-5248, Vol. 17, no 7, 664-677 p.Article in journal (Refereed) PublishedText
Abstract [en]

The diagnostic scaling concept, introduced for the streamwise turbulence intensity in wall-bounded turbulent flows (Alfredsson, Segalini and Örlü, Phys. Fluids 2011;23:041702), is here extended and generalised not only for the higher even-order central statistical moments, but also for the odd moments and thereby the probability density distribution of the streamwise velocity fluctuations. Turbulent boundary layer data up to a friction Reynolds number of 60,000 are employed and demonstrate the feasibility of the diagnostic scaling for the data throughout the logarithmic and wake regions. A comparison with the generalised logarithmic law for even-order moments by Meneveau and Marusic (J. Fluid Mech. 2013;719:R1) based on the attached-eddy hypothesis, is reported. The diagnostic plot provides an apparent Reynolds-number-independent scaling of the data, and is exploited to reveal the functional dependencies of the constants needed in the attached-eddy-based model. In particular, the invariance of the lowest order diagnostic scaling poses an intriguing incompatibility with the asymptotic constancy of the Townsend–Perry constant.

Place, publisher, year, edition, pages
Taylor & Francis, 2016. Vol. 17, no 7, 664-677 p.
Keyword [en]
turbulent boundary layers, Turbulent flows
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:kth:diva-187183DOI: 10.1080/14685248.2016.1169282ISI: 000380171000003ScopusID: 2-s2.0-84964329594OAI: oai:DiVA.org:kth-187183DiVA: diva2:929850
Note

QC 20160830

Available from: 2016-05-20 Created: 2016-05-18 Last updated: 2016-08-30Bibliographically approved

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Örlü, RamisSegalini, AntonioAlfredsson, P. Henrik
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