Cascade Model for Planetesimal Formation by Turbulent Clustering

Abstract

We use a newly developed cascade model of turbulent concentration of particles in protoplanetary nebulae to calculate several properties of interest to the formation of primitive planetesimals and to the meteorite record. The model follows, and corrects, calculations of the primary planetesimal Initial Mass Function (IMF) by Cuzzi et al. (2010), in which an incorrect cascade model was used. Here we use the model of Hartlep et al. ( 2017), which has been validated against several published numerical simulations of particle concentration in turbulence. We find that, for a range of nebula and particle properties, planetesimals may be "born big", formed as sandpiles with diameters in the 10 − 100 km range, directly from freely floating particles. The IMFs have a modal nature, with a well-defined peak rather than a powerlaw size dependence. Predictions for the inner and outer nebula behave similarly in these regards, and observations of inner and outer nebula primitive bodies support such modal IMFs. Also, we present predictions of local particle concentrations on several lengthscales in which particles "commonly" find themselves, which have significance for meteoritical observations of the redox state and isotopic fractionation in regions of chondrule formation. An important difference between these results, and those of Cuzzi et al. (2010), is that particle growth-by-sticking must proceed to at least the 1−few cm radius range for the IMF and meteoritical properties to be most plausibly satisfied. That is, as far as the inner nebula goes, the predominant "particles" must be aggregates of chondrules (or chondrule-size precursors) rather than individual chondrules themselves.

Effect of pebble flux-regulated planetesimal formation on giant planet formation

“…Many different planetesimal formation prescriptions can therefore be parameterized in this way. Wheter in the framework of turbulent clustering (Cuzzi et al 2010;Hartlep & Cuzzi 2020), streaming instabilities (Johansen et al 2009;Schäfer et al 2017), local trapping in zonal flows (Johansen et al 2007(Johansen et al , 2011Dittrich et al 2013;Drążkowska & Alibert 2017), or in vortices (Raettig et al 2015;Lyra et al 2018), the formation is always limited by the number of fresh pebbles that a region receives after consuming the locally available pebbles. Our parameterization is thus by definition model independent.…”

Planet Formation

“…Great advances on planetesimal formation have been made in the last 15 years, as it was discovered that dust can form clumps due to a number of hydrodynamical effects [e.g., 24,39,49,50,123]. The most promising and deeply studied of these effects is called the "streaming instability".…”

“…Regardless of the actual dust-clumping mechanism, when a clumps becomes dense enough the dust remains bound by self-gravity against diffusion generated by turbulence and eventually settles to form a macroscopic object, with a characteristic size of ∼ 100 km. The problem is that efficient dust clumping can be triggered only if (i) the dust particles are large enough (decimeter-size, or Stokes' number of order unity) or (ii) the dust/gas ratio is a few times that of the average protosolar material [e.g., 39,51,122].…”

Understanding the trans-Neptunian Solar system; Reconciling the results of serendipitous stellar occultations and the inferences from the cratering record.

“…Thus, well constrained measurements of the size-number distribution of trans-Neptunian objects, especially Cold Classicals, at sizes well below ∼ 50 km could provide strong support for models of their formation; planetesimal formation via the streaming instability (Youdin & Goodman 2005;Johansen et al 2007) is currently generally seen as the most promising mechanism for forming planetesimals at these sizes (Raymond & Morbidelli 2020), and makes clear predictions for the expected size-number distribution below the primordial break in the size-number distribution (Simon et al 2016(Simon et al , 2017. Conversely, of course, such measurements might instead provide evidence of a competing mechanism, such as fluffy aggregate growth (Arakawa & Nakamoto 2016), collisional pebble agglomeration (Shannon et al 2016), or turbulent clustering (Cuzzi et al 2010(Cuzzi et al , 2016Hartlep & Cuzzi 2020).…”