Inertial particles in a Kolmogorov channel flow
ORAL
Abstract
We investigate, by means of analytical and numerical methods, the effects of heavy particles on the linear stability and on the turbulent drag of a Kolmogorov channel flow.
Particles are modeled in the framework of an Eulerian two-way coupling model: a continuum density transported by a compressible velocity field which exchanges momentum with the fluid phase.
In the case of laminar flow, we find that particles can either stabilize or destabilize the flow depending on the particle Stokes number and on the mass fraction.
In the case of a turbulent Kolmogorov flow, we find that particles always reduce the mean flow with respect to the pure fluid case and therefore enhance the drag coefficient.
Turbulence suppression is observed to be stronger for particles of smaller inertia. This surprising result is understood by mapping the equations for dusty flow to a Newtonian flow with an effective forcing rescaled by the increased fluid density.
Particles are modeled in the framework of an Eulerian two-way coupling model: a continuum density transported by a compressible velocity field which exchanges momentum with the fluid phase.
In the case of laminar flow, we find that particles can either stabilize or destabilize the flow depending on the particle Stokes number and on the mass fraction.
In the case of a turbulent Kolmogorov flow, we find that particles always reduce the mean flow with respect to the pure fluid case and therefore enhance the drag coefficient.
Turbulence suppression is observed to be stronger for particles of smaller inertia. This surprising result is understood by mapping the equations for dusty flow to a Newtonian flow with an effective forcing rescaled by the increased fluid density.
–
Publication: A. Sozza, M. Cencini, S. Musacchio, G. Boffetta<br>"Drag enhancement in a dusty Kolmogorov flow"<br>Physical Review Fluids 5, 094302 (2020).
Presenters
-
Guido Boffetta
University of Torino (Italy)
Authors
-
Guido Boffetta
University of Torino (Italy)
-
Massimo Cencini
ISC-CNR (Italy), Institute for complex systems CNR, Rome, Italy
-
Stefano Musacchio
University of Torino (Italy)
-
Alessandro Sozza
ENS-Lyon (France)