The OSIRIS-REx mission collected a sample from the surface of the asteroid (101955) Bennu in October 2020. Here we study the impact of the OSIRIS-REx Touch-and-Go Sampling Acquisition Mechanism (TAGSAM) interacting with the surface of an asteroid in the framework of granular physics. Traditional approaches to estimating the penetration depth of a projectile into a granular medium include force laws and scaling relationships formulated from laboratory experiments in terrestrial-gravity conditions. However, it is unclear that these formulations extend to the OSIRIS-REx scenario of a 1300-kg spacecraft interacting with regolith in a microgravity environment. We studied the TAGSAM interaction with Bennu through numerical simulations using two collisional codes, pkdgrav and GDC-i. We validated their accuracy by reproducing the results of laboratory impact experiments in terrestrial gravity. We then performed TAGSAM penetration simulations varying the following geotechnical properties of the regolith: packing fraction (P), bulk density, inter-particle cohesion (σc), and angle of friction (ɸ). We find that the outcome of a spacecraft-regolith impact has a non-linear dependence on packing fraction. Closely packed regolith (P≳0.6) can effectively resist the penetration of TAGSAM if ɸ≳28° and/or σc≳50 Pa. For loosely packed regolith (P≲0.5), the penetration depth is governed by a drag force that scales with impact velocity to the 4/3 power, consistent with energy conservation. We discuss the importance of low-speed impact studies for predicting and interpreting spacecraft-surface interactions. We show that these low-energy events also provide a framework for interpreting the burial depths of large boulders in asteroidal regolith.

Atmospheric drag is one of the primary sources of error in the orbit determination and prediction of satellites in the low altitude LEO regime. Accurate modeling of the drag force is limited by uncertainties in the atmospheric density model used in the filter and the assumption of a constant drag coefficient, the so-called ‘cannonball’ model. Over the last two decades, various advances in density and drag-coefficient modeling have been made possible through the development of empirical and physics-based dynamical calibration techniques and machine-learning methods respectively. But even with high-fidelity models for density and drag coefficient, systematic uncertainties can remain in both due to the lack of temporal and spatial resolution of data and insufficient knowledge of parameters that feed into these models. In this work, we develop an estimation-based Fourier expansion model that can provide corrections to the nominal values of density and drag coefficient during the orbit determination process. In an earlier work (Ray et al., 2018), we demonstrated improved orbit prediction performance over the standard cannonball model with Fourier series expansions of the drag coefficient in body frame and orbit frame of a satellite. Whereas a body-fixed Fourier model captures the dependence of the drag coefficient on satellite attitude, the orbit-fixed model corrects for periodic changes in the gas-surface interaction in orbit. Since changes in the gas-surface interaction parameters in orbit are highly correlated with atmospheric density, any existing errors in the density are absorbed in the estimated orbit-fixed coefficients. Here, we derive a body-orbit Fourier model such that the orbit-fixed terms provide corrections for combined error variations of density and drag coefficient in orbit while the body-fixed terms account for the drag coefficient attitude dependence. We analyze the performance of the proposed approach with various atmospheric models such as NRLMSISE-00 (Picone et al., 2002), JB08 (Bowman et al., 2008), HASDM (Storz et al., 2002) and densities derived by Mehta et al. (2017) for varying geomagnetic conditions for the GRACE satellite.