Flow, Turbulence and Combustion

, Volume 97, Issue 4, pp 1017–1046 | Cite as

Scrutinizing URANS in Shedding Flows: The Case of Cylinder in Cross-Flow in the Subcritical Regime

  • E. Palkin
  • R. Mullyadzhanov
  • M. Hadžiabdić
  • K. Hanjalić


To unravel the widespread perception that the RANS (Reynolds-averaged Navier-Stokes) concept is unreliable in predicting the dynamics of separated flows, we assessed the performance of two RANS closure levels, the linear eddy-viscosity (LEVM) and the second-moment (Reynolds stress, RSM) approaches in a massively separated generic flow over a bluff body. Considered is the canonical, zero-turbulence, cross-flow over an infinite cylinder with reference to our LES and the available DNS and experiments at two Reynolds numbers, Re = 3.9 × 103 and 1.4 × 105, both within the sub-critical regime with laminar separation. Both models capture successfully the vortex shedding frequency, but the low frequency modulations are detected only by the RSM. At high Reynolds numbers the RSM is markedly superior to the LEVM showing very good agreement with the LES and experimental data. The RSM, accounting naturally for the stress anisotropy and phase lag between the stress and strain eigenvectors, is especially successful in reproducing the growth rate of the turbulent kinetic energy in the initial shear layer which proved to be crucial for accurate prediction of the separation-induced transition. A scrutiny of the unsteady RANS (URANS) stress terms based on the conditional phase-averaged LES data shows a remarkable similarity of the normalized coherent and stochastic (modeled) stress components for the two Reynolds numbers considered. The mixed (cross) correlations, while non-negligible at the low Re number, diminish fast relative to the stochastic ones with increasing Reynolds number and, in the whole, are not significant to undermine the URANS concept and its applicability to high Re flows of industrial relevance.


URANS LES Cylinder Sub-critical regime 



This work is funded by Russian Science Foundation grant No. 14-29-00203. The computational resources are provided by Siberian Supercomputer Center SB RAS (Novosibirsk), Novosibirsk State University Computing Center (Novosibirsk) and Joint Supercomputer Center RAS (Moscow). The authors thank B. Cantwell, I. Rodríguez, O. Lehmkuhl and E. Lamballais for sharing their numerical and experimental data and the referees for many valuable suggestions.


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • E. Palkin
    • 1
    • 2
  • R. Mullyadzhanov
    • 1
    • 2
  • M. Hadžiabdić
    • 3
  • K. Hanjalić
    • 2
    • 4
  1. 1.Institute of Thermophysics SB RASNovosibirskRussia
  2. 2.Novosibirsk State UniversityNovosibirskRussia
  3. 3.International University of SarajevoIlidźaBosnia and Herzegovina
  4. 4.Delft University of TechnologyDelftThe Netherlands

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