Contour Shape Dependency of Circulation Statistics in Homogeneous and Isotropic Turbulence

ORAL

Abstract

Statistical moments of the turbulent circulation are complex geometry-dependent functionals of closed oriented contours and present a hard challenge for theoretical understanding. Conveniently defined circulation moment ratios, however, are empirically known to have appreciable geometric dependency only at lower moment orders and for contours which are sized near the bottom of the inertial range, in the situation where they span minimal surfaces of equivalent areas. Resorting to ideas addressed in the framework of the vortex gas model of circulation statistics, which integrates structural and multifractal aspects of the turbulent velocity field, we are able to reproduce, with reasonable accuracy, the observed contour shape dependency of circulation moment ratios, up to high order statistics. A key phenomenological point in our discussion is the assumption that the energy dissipation field, closely related to the local density of thin vortex tubes, is sharply bounded from above at finite Reynolds numbers.

*K.I. thanks P.K. Yeung for his sustained collaboration on the DNS data and the National Science Fundation (NSF) for partial support, via Grant ACI-1640771 at the Georgia Institute of Technology. The computations were performed using supercomputing resources provided through the Extreme Science and Engineering Discovery Environment (XSEDE) consortium (which is funded by NSF) at the Texas Advanced Computing Center at the University of Texas (Austin) and the Blue Waters Project at the National Center for Supercomputing Applications at the University of Illinois (Urbana–Champaign). L.M. thanks the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for partial support, via Grant 311012/2022-1.

Presenters

  • Luca Moriconi

    • Universidade Federal do Rio de Janeiro

Authors

  • Luca Moriconi

    • Universidade Federal do Rio de Janeiro
  • Kartik P Iyer

    • Michigan Technological University