Abstract
We investigate Reynolds number effects in shockwave/turbulent boundary-layer interactions (STBLI) with strong mean flow separation. Three wall-resolved large-eddy simulations (LES) are performed for this purpose, with different Reynolds number but otherwise equal flow parameters and simulation setup. The resulting LES data covers more than a decade of friction Reynolds number. The high-Reynolds case, with friction Reynolds number Reτ = 5118 and momentum Reynolds number Reθ = 26438 at the virtual impingement point without the shock, features a turbulent boundary layer with clear inner and outer scale separation. All STBLI simulations exhibit substantial flow reversal and have been integrated for a very long time (90 flow-through times of the full domain length) to properly resolve low-frequency dynamics. Instantaneous and mean flow as well as spectral features are described in detail, together with a modal analysis of the three-dimensional streamwise velocity, streamwise vorticity and pressure fields.
Original language | English |
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Number of pages | 6 |
Publication status | Published - 2022 |
Event | 12th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2022 - Osaka, Virtual, Japan Duration: 19 Jul 2022 → 22 Jul 2022 |
Conference
Conference | 12th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2022 |
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Country/Territory | Japan |
City | Osaka, Virtual |
Period | 19/07/22 → 22/07/22 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
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Supplementary material to the publication 'Reynolds number effects in shock-wave/turbulent boundary-layer interactions'.
Laguarda Sanchez, L. (Creator), Schrijer, F. F. J. (Creator), van Oudheusden, B. W. (Creator) & Hickel, S. (Creator), TU Delft - 4TU.ResearchData, 11 Sept 2023
DOI: 10.4121/7F9D8B26-0F1D-4BC0-895C-E36394891C62
Dataset/Software: Dataset