Modelling the light-scattering properties of a planetary-regolith analog sample

Abstract : Solving the scattering properties of asteroid surfaces can be made cheaper, faster, and more accurate with reliable physics-based electromagnetic scattering programs for large and dense random media. Existing exact methods fail to produce solutions for such large systems and it is essential to develop approximate methods. Radiative transfer (RT) is an approximate method which works for sparse random media such as atmospheres fails when applied to dense media. In order to make the method applicable to dense media, we have developed a radiative-transfer coherent-backscattering method (RT-CB) with incoherent interactions. To show the current progress with the RT-CB, we have modeled a planetary-regolith analog sample. The analog sample is a low-density agglomerate produced by random ballistic deposition of almost equisized silicate spheres studied using the PROGRA2-surf experiment. The scattering properties were then computed with the RT-CB assuming that the silicate spheres were equisized and that there were a Gaussian particle size distribution. The results were then compared to the measured data and the intensity plot is shown below. The phase functions are normalized to unity at the 40-deg phase angle. The tentative intensity modeling shows good match with the measured data, whereas the polarization modeling shows discrepancies. In summary, the current RT-CB modeling is promising, but more work needs to be carried out, in particular, for modeling the polarization
Document type :
Poster communications
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https://hal-insu.archives-ouvertes.fr/insu-01676887
Contributor : Catherine Cardon <>
Submitted on : Saturday, January 6, 2018 - 5:14:31 PM
Last modification on : Tuesday, May 14, 2019 - 11:09:41 AM

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  • HAL Id : insu-01676887, version 1

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Timo Vaisanen, Johannes Markkanen, Edith Hadamcik, Anny Chantal Levasseur-Regourd, Jérémie Lasue, et al.. Modelling the light-scattering properties of a planetary-regolith analog sample. AGU 2017 Fall Meeting, Dec 2017, New Orleans, United States. ⟨insu-01676887⟩

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