Ejecta cloud distributions for the statistical analysis of impact cratering events onto asteroids' surfaces: a sensitivity analysis

TL;DR

This paper develops a statistical model of ejecta cloud distributions from asteroid impact events, analyzing how different assumptions affect ejecta evolution and impact outcomes.

Contribution

It introduces a continuum distribution model combining probability density functions for ejecta size, speed, and angles, and assesses the sensitivity of ejecta fate to various modeling assumptions.

Findings

Some modeling assumptions significantly influence ejecta impact and escape rates.

Different distribution types and ejection speed models affect fragment impact distribution.

The methodology enables efficient statistical analysis of ejecta evolution.

Abstract

This work presents the model of an ejecta cloud distribution to characterise the plume generated by the impact of a projectile onto asteroids surfaces. A continuum distribution based on the combination of probability density functions is developed to describe the size, ejection speed, and ejection angles of the fragments. The ejecta distribution is used to statistically analyse the fate of the ejecta. By combining the ejecta distribution with a space-filling sampling technique, we draw samples from the distribution and assigned them a number of \emph{representative fragments} so that the evolution in time of a single sample is representative of an ensemble of fragments. Using this methodology, we analyse the fate of the ejecta as a function of different modelling techniques and assumptions. We evaluate the effect of different types of distributions, ejection speed models, coefficients, etc. The results show that some modelling assumptions are more influential than others and, in some cases, they influence different aspects of the ejecta evolution such as the share of impacting and escaping fragments or the distribution of impacting fragments on the asteroid surface.