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Energy transfer mechanisms in adverse pressure gradient turbulent boundary layers: production and inter-component redistribution

  • Taygun R. Gungor
  • , Yvan Maciel
  • , Ayse G. Gungor*
  • *Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

32 Atıf (Scopus)

Özet

Production and inter-component redistribution of turbulence in adverse pressure gradient (APG) turbulent boundary layers (TBLs) with small and large velocity defects are investigated, along with the structures playing a role in these energy transfer mechanisms. We examine the wall-normal and spectral distributions of energy, production and pressure-strain in APG TBLs, and compare these distributions with those in canonical flows. It is found that the spectral distributions of production and pressure-strain are not affected profoundly by an increase of the velocity defect, although the energy spectra change drastically in the inner layer of the large-defect APG TBL. In the latter, the signature of the inner-layer streaks is absent from the energy spectra. In the outer layer, energetic, production and pressure-strain structures appear to change from wall-attached to wall-detached structures with increasing velocity defect. Despite this, the two-dimensional spectral distributions have similar shapes and wavelength aspect ratios of the peaks in all these flows. Therefore, the conclusion is that the mechanisms responsible for turbulence production and inter-component energy transfer may remain the same within each layer in all these flows. It is the intensity of these mechanisms within one layer that changes with velocity defect, because of the local mean shear variation.

Orijinal dilİngilizce
Makale numarasıA5
DergiJournal of Fluid Mechanics
Hacim948
DOI'lar
Yayın durumuYayınlandı - 10 Eki 2022

Bibliyografik not

Publisher Copyright:
© The Author(s), 2022. Published by Cambridge University Press

Finansman

We acknowledge PRACE for awarding us access to Marconi100 at CINECA, Italy, and Calcul Quëbec (www.calculquebec.ca) and Compute Canada (www.computecanada.ca) for awarding us access to the Niagara HPC server. The authors would like to thank Myoungkyu Lee and Robert D. Moser for providing their channel flow data. T.R.G. and A.G.G. were supported by the research funds of Istanbul Technical University (project nos MGA-2019-42227 and MDK-2018-41689). T.R.G. and Y.M. acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), project no. RGPIN-2019-04194.

FinansörlerFinansör numarası
CINECA
Compute Canada
Natural Sciences and Engineering Research Council of CanadaRGPIN-2019-04194
Partnership for Advanced Computing in Europe AISBL
Istanbul Teknik ÜniversitesiMDK-2018-41689, MGA-2019-42227

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