Compacted aggregates from numerical simulations compared to Rosetta collected particles
Abstract
The Rosetta space mission includes three main instruments for solid dust particles analysis. The combined
microscope and mass spectrometer COSIMA (Cometary Secondary Ion Mass Analyser) [1], the atomic force
microscope MIDAS (Micro-Imaging Dust Analysis System) [2], and the impact detector GIADA (Grain Impact
Analyser and Dust Accumulator) [3]. These three instruments provide complementary insights into the dust
particles properties thanks to their different approaches and resolution ranges (10nm to 1mm). GIADA and
MIDAS observed a major contribution from compact dust aggregates together with a population of porous
particles with a low fractal dimension (Df ~ 1.7 for MIDAS [4]) [5, 6]. Such a fractal dust component of the
nucleus and its properties give constraints on the formation of comets in the early solar system [5].
In this work, we analyse results from a simple numerical model of dust aggregates compaction and compare them
with COSIMA images of collected aggregates to assess the initial physical properties of the dust populations. We
consider 4 different kinds of fractal aggregates presenting different initial fractal dimensions (Df ~ 1.8/2.1/2.5/3)
based on their aggregation processes (diffusion limited or reaction limited aggregations, depending on the surface
sticking probabilities of the monomers, and particle-cluster or cluster-cluster aggregations).
We find that the aspect ratio distribution observed by COSIMA may be explained either by compacting two
different initial families with low and high fractal dimensions and the same cohesive strength between monomers,
or by compacting a single type of particles (with an aggregation process like DLPA) however with a large range
of internal cohesive strengths or collection velocities.
References: [1] Kissel, J. et al. (2007) SSR, 128(1), 823-867. [2] Riedler, W. et al. (2007) SSR, 128(1-4),
869-904. [3] Colangeli, L. et al. (2007) SSR, 128(1-4), 803-821. [4] Mannel, T. et al. (2016) MNRAS, 462(S1),
304-311. [5] Fulle, M. and Blum, J. (2017), MNRAS, 469(S2), 39-44 [6] Fulle, M. et al. (2017) MNRAS 469(S2),
45–49