Scale dependence of the alignment between strain rate and rotation in turbulent shear flow

D. Fiscaletti, G. E. Elsinga, Antonio Attili, Fabrizio Bisetti, O. R. H. Buxton

Research output: Contribution to journalArticlepeer-review

Abstract

The scale dependence of the statistical alignment tendencies of the eigenvectors of the strain-rate tensor e(i), with the vorticity vector omega, is examined in the self-preserving region of a planar turbulent mixing layer. Data from a direct numerical simulation are filtered at various length scales and the probability density functions of the magnitude of the alignment cosines between the two unit vectors vertical bar e(i) . (omega) over cap vertical bar are examined. It is observed that the alignment tendencies are insensitive to the concurrent large-scale velocity fluctuations, but are quantitatively affected by the nature of the concurrent large-scale velocity-gradient fluctuations. It is confirmed that the small-scale (local) vorticity vector is preferentially aligned in parallel with the large-scale (background) extensive strain-rate eigenvector e(1), in contrast to the global tendency for omega to be aligned in parallelwith the intermediate strain-rate eigenvector [Hamlington et al., Phys. Fluids 20, 111703 (2008)]. When only data from regions of the flow that exhibit strong swirling are included, the so-called high-enstrophy worms, the alignment tendencies are exaggerated with respect to the global picture. These findings support the notion that the production of enstrophy, responsible for a net cascade of turbulent kinetic energy from large scales to small scales, is driven by vorticity stretching due to the preferential parallel alignment between omega and nonlocal e(1) and that the strongly swirling worms are kinematically significant to this process.
Original languageEnglish (US)
JournalPhysical Review Fluids
Volume1
Issue number6
DOIs
StatePublished - Oct 24 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We acknowledge valuable support from KAUST Supercomputing Laboratory in the form of assistance with code development and computational time on the IBM System Blue Gene/P

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