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11:30
15 mins
PREFERRENTIAL CONCENTRATION OF PARTICLES IN PROTOPLANETARY NEBULA TURBULENCE
Thomas Hartlep, Jeffrey Cuzzi
Session: Geophysical and astrophysical turbulence 3
Session starts: Friday 28 August, 10:30
Presentation starts: 11:30
Room: Room C
Thomas Hartlep (Bay Area Environmental Research Institute)
Jeffrey Cuzzi (NASA Ames Research Center)
Abstract:
Preferential concentration in turbulence is a process that causes inertial particles to cluster in regions of high strain (in-between high vorticity regions), with specifics depending on their stopping time or Stokes number. This process is thought to be of importance in various problems including cloud droplet formation and aerosol transport in the atmosphere, sprays, and also in the formation of asteroids and comets in protoplanetary nebulae.
In protoplanetary nebulae, the initial accretion of primitive bodies from freely-floating particles remains a problematic subject. Traditional growth-by-sticking models encounter a formidable ``meter-size barrier'' [1] in turbulent nebulae. One scenario that can lead directly from independent nebula particulates to large objects, avoiding the problematic m-km size range, involves formation of dense clumps of aerodynamically selected, typically mm-size particles in protoplanetary turbulence. There is evidence that at least the ordinary chondrite parent bodies were initially composed entirely of a homogeneous mix of such particles generally known as ``chondrules'' [2]. Thus, while it is arcane, turbulent preferential concentration acting directly on chondrule size particles are worthy of deeper study.
Here, we present the statistical determination of particle multiplier distributions from numerical simulations of particle-laden isotopic turbulence, and a cascade model for modeling turbulent concentration at lengthscales and Reynolds numbers not accessible by numerical simulations. We find that the multiplier distributions are scale dependent at the very largest scales but have scale-invariant properties under a particular variable normalization at smaller scales.