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On determining characteristic length scales in pressure-gradient turbulent boundary layers
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, Centres, SeRC - Swedish e-Science Research Centre. KTH, School of Engineering Sciences (SCI), Mechanics.ORCID iD: 0000-0001-9833-9560
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. KTH, Centres, SeRC - Swedish e-Science Research Centre.ORCID iD: 0000-0001-9627-5903
2016 (English)In: Physics of fluids, ISSN 1070-6631, E-ISSN 1089-7666, Vol. 28Article in journal (Refereed) Published
Abstract [en]

In the present work we analyze three commonly used methods to determine the edge of pressure gradient turbulent boundary layers: two based on composite profiles, the one by Chauhan et al. (Fluid Dyn. Res. 41:021401, 2009) and the one by Nickels (J. Fluid Mech. 521:217–239, 2004), and the other onebased on the condition of vanishing mean velocity gradient. Additionally, a new method is introduced based on the diagnostic plot concept by Alfredsson et al. (Phys. Fluids 23:041702, 2011). The boundary layers developing over the suction and pressure sides of a NACA4412 wing section, extracted from a directnumerical simulation at chord Reynolds number Rec = 400, 000, is used as the test case, besides other numerical and experimental data from favorable, zero and adverse pressure-gradient flat-plate turbulent boundary layers. We find that all the methods produce robust results with mild or moderate pressure gradients, although the composite-profile techniques require data preparation, including initial estimations of fitting parameters and data truncation. Stronger pressure gradients (with a Rotta–Clauser pressure-gradient parameter β larger than around 7) lead to inconsistent results in all the techniques except the diagnosticplot. This method also has the advantage of providing an objective way of defining the point where the mean streamwise velocity is 99% of the edge velocity, and shows consistent results in a wide range of pressure gradient conditions, as well as flow histories. Collapse of intermittency factors obtained from a wide range of pressure-gradient and Re conditions on the wing further highlightsthe robustness of the diagnostic plot method to determine the boundary layert hickness (equivalent to δ99 ) and the edge velocity in pressure gradient turbulent boundary layers.

Place, publisher, year, edition, pages
American Institute of Physics (AIP), 2016. Vol. 28
National Category
Fluid Mechanics and Acoustics
Identifiers
URN: urn:nbn:se:kth:diva-185269DOI: 10.1063/1.4947532 ScopusID: 2-s2.0-84966546523OAI: oai:DiVA.org:kth-185269DiVA: diva2:919833
Note

QC 20160526

Available from: 2016-04-15 Created: 2016-04-15 Last updated: 2016-05-26Bibliographically approved
In thesis
1. Simulations of turbulent boundary layers with suction and pressure gradients
Open this publication in new window or tab >>Simulations of turbulent boundary layers with suction and pressure gradients
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The focus of the present licentiate thesis is on the effect of suction and pressure gradients on turbulent boundary-layer flows, which are investigated separately through performing numerical simulations.The first part aims at assessing history and development effects on adverse pressure-gradient (APG) turbulent boundary layers (TBL). A suitable set-up was developed to study near-equilibrium conditions for a boundary layer developingon a flat plate by setting the free-stream velocity at the top of the domain following a power law. The computational box size and the correct definition of the top-boundary condition were systematically tested. Well-resolved large-eddy simulations were performed to keep computational costs low. By varying the free-stream velocity distribution parameters, e.g. power-law exponent and virtual origin, pressure gradients of different strength and development were obtained. The magnitude of the pressure gradient is quantified in terms of the Clauser pressure-gradient parameter β. The effect of the APG is closely related to its streamwise development, hence, TBLs with non-constant and constant β were investigated. The effect was manifested in the mean flow through a much more pronounced wake region and in the Reynolds stresses through the existence of an outer peak. The terms of the turbulent kinetic energy budgets indicate the influence of the APG on the distribution of the transfer mechanism across the boundary layer. Stronger and more energetic structures were identified in boundary layers with relatively stronger pressure gradients in their development history. Due to the difficulty of determining the boundary-layer thickness in flows with strong pressure gradients or over a curvedsurface, a new method based on the diagnostic-plot concept was introduced to obtain a robust estimation of the edge of a turbulent boundary layer.

In the second part, large-eddy simulations were performed on temporally developing turbulent asymptotic suction boundary layers (TASBLs). Findings from previous studies about the effect of suction could be confirmed, e.g. the reduction of the fluctuation levels and Reynolds shear stresses. Furthermore, the importance of the size of the computational domain and the time development were investigated. Both parameters were found to have a large impact on the results even on low-order statistics. While the mean velocity profile collapses in the inner layer irrespective of box size and development time, a wake region occurs for too small box sizes or early development time and vanishes once sufficiently large domains and/or integration times are chosen. The asymptotic state is charactersized by surprisingly thick boundary layers even for moderateReynolds numbers Re (based on free-stream velocity and laminar displacement thickness); for instance, Re = 333 gives rise to a friction Reynolds number Reτ = 2000. Similarly, the flow gives rise to very large structures in the outer region. These findings have important ramifications for experiments, since very large facilities are required to reach the asymptotic state even for low Reynolds numbers.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2016. 37 p.
Series
TRITA-MEK, ISSN 0348-467X ; 2016:07
Keyword
boundary layers, near-wall turbulence, history effects, asymptotic suction boundary layers, large-eddy simulation
National Category
Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:kth:diva-185275 (URN)978-91-7595-934-4 (ISBN)
Presentation
2016-05-12, D3, Lindstedtsvägen 5, Stockholm, 10:15 (English)
Opponent
Supervisors
Note

QC 20160418

Available from: 2016-04-18 Created: 2016-04-15 Last updated: 2016-04-18Bibliographically approved

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Bobke, AlexandraÖrlü, RamisSchlatter, Philipp
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