The mechanism of unsteady wake transition behind large depth-ratio wall-mounted prisms

ORAL

Abstract

The onset of wake unsteadiness for small aspect-ratio (height-to-width) wall-mounted prisms depends on both flow and geometrical parameters, i.e., depth-ratio (length-to-width) and Reynolds number (Re). While past studies have characterized the onset of unsteady wake for infinitely-span and large aspect-ratio (finite span) wall-mounted prisms, the effect of depth-ratio remains unexplored. As such, we numerically investigate the onset unsteady flow in the wake of wall-mounted finite prisms with an aspect-ratio of 1 and varying depth-ratios between 0.016 and 4 at Re=50-2500. The minimum depth-ratio considered here represents the special case of a wall-mounted thin flat plate. Preliminary results indicate that the onset of unsteady wake for wall-mounted thin flat plate occurs at Re=190, while that of a wall-mounted cube occurs at Re=400. Transition to unsteady wake for prisms with large depth-ratio occurs at Re=600. The onset of unsteady wake is characterized by symmetric hairpin-like vortex shedding, which leads to an oscillatory drag force and separating side-edge shear-layers. Moreover, threshold Reynolds number of transition to unsteady wake for wall-mounted prisms is significantly larger than that of finite-suspended prisms and thin flat plates. It is known that transition to unsteady wake occurs due to Hopf-bifurcation for suspended bluff bodies, whereas the present results indicate a different mechanism that governs this phenomenon for wall-mounted prisms. Thus, we aim to identify and characterize the mechanism of transition to unsteady wake for wall-mounted prisms with changing depth-ratio. Furthermore, we aim to characterize the various regimes of unsteady wake to fully understand the transition-to-turbulence wake phenomenon induced by the increasing depth-ratio in wall-mounted prisms.

*This research has received support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and Alberta Innovates. The computational analysis was completed using Digital Research Alliance of Canada clusters.

Presenters

  • Shubham Goswami

    • University of Alberta

Authors

  • Shubham Goswami

    • University of Alberta
  • Arman Hemmati

    • Univ of Alberta
    • University of Alberta