The MMX Rover: Performing In-Situ Surface Investigations on Phobos

The MMX Rover: Performing in-situ Surface Investigations on Phobos

Patrick Michel (  [email protected] ) CNRS Délégation Côte d'Azur https://orcid.org/0000-0002-0884-1993 Stephan Ulamec DLR: Deutsches Zentrum fur Luft- und Raumfahrt Ute Boettger DLR Matthias Grott DLR Berlin: Deutsches Zentrum fur Luft- und Raumfahrt DLR Standort Berlin Naomi Murdoch ISAE-SUPAERO Pierre Vernazza LAM: Laboratoire d'Astrophysique de Marseille Cecily Sunday ISAE-SUPAERO Yun Zhang UCA: Universite Cote d'Azur Rudy Valette CEMEF: Centre de mise en forme des materiaux Romain Castellani CEMEF: Centre de mise en forme des materiaux Jens Biele DLR: Deutsches Zentrum fur Luft- und Raumfahrt Simon Tardivel French Space Agency: CNES Olivier Groussin LAM: Laboratoire d'Astrophysique de Marseille Laurent Jorda LAM: Laboratoire d'Astrophysique de Marseille Joerg Knollenberg DLR: Deutsches Zentrum fur Luft- und Raumfahrt Jan Thimo Grundmann DLR: Deutsches Zentrum fur Luft- und Raumfahrt Denis Arrat French Space Agency: CNES Gabriel Pont French Space Agency: CNES Stéphane Mary French Space Agency: CNES Markus Grebenstein DLR: Deutsches Zentrum fur Luft- und Raumfahrt Hirdy Miyamoto University of Tokyo: Tokyo Daigaku Tomoki Nakamura Tohoku University Graduate School of Science Faculty of Science: Tohoku Daigaku Daigakuin Rigaku Kenkyuka Rigakubu Koji Wada Chiba Institute of Technology: Chiba Kogyo Daigaku Kent Yoshikawa JAXA Kiyoshi Kuramoto Hokkaido University: Hokkaido Daigaku

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Keywords: Camera, Numerical Modeling, Phobos, Radiometer, Raman Spectrometer, Regolith, Regolith Dynamics,101 Thermal Inertia, Rover102

Posted Date: January 15th, 2021

DOI: https://doi.org/10.21203/rs.3.rs-139920/v1

License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License 1 2 3 4 5 1 The MMX rover: performing in-situ surface investigations on 6 7 8 2 Phobos 9 10

11 ∗ 12 3 Patrick Michel , UniversitéCôte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, 13 14 4 Nice, 06304, France, [email protected] 15 16 5 17 18 6 Stephan Ulamec, Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Linder Höhe, Cologne, 51147, 19 20 7 Germany, [email protected] 21

22 8 23 24 9 Ute Boettger, Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institute of Optical Sensor Sys- 25 26 27 10 tems, 12489 Berlin, Rutherfordstr. 2, Germany, [email protected] 28 29 11 30 31 12 Matthias Grott, Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Planetenforschungn 32 33 13 Rutherfordstrasse 2, 12489 Berlin, Germany, [email protected] 34 35 14 36 37 15 Naomi Murdoch, ISAE-SUPAERO, Universitéde Toulouse, DEOS/Space Systems for Planetary Appli- 38 39 16 cations, 10 avenue Edouard Belin, BP 54032, 31055 Toulouse Cedex 4, France, Naomi.MURDOCH@isae- 40 41 17 supaero.fr 42 43 18 44 45 46 19 Pierre Vernazza, Aix Marseille Université, CNRS, CNES, Laboratoire d’Astrophysique de Marseille, Mar- 47 48 20 seille, France, [email protected] 49 50 21 51 52 22 Cecily Sunday, Universitéde Toulouse, DEOS/Space Systems for Planetary Applications, 10 avenue 53 54 23 Edouard Belin, BP 54032, 31055 Toulouse Cedex 4, France, [email protected] 55 56 24 57 58 25 Yun Zhang, UniversitéCôte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, Nice, 59 60 26 06304, France, [email protected] 61 62 63 64 1 65 27 1 2 28 Rudy Valette, Mines ParisTech, PSL Research University, CEMEF, Centre for Material Forming, CNRS 3 4 29 UMR 7635, CS 10207 rue Claude Daunesse, 06904 Sophia Antipolis Cedex, France, rudy.valette@mines- 5 6 30 paristech.fr 7 8 9 31 10 11 32 Romain Castellani, Mines ParisTech, PSL Research University, CEMEF, Centre for Material Form- 12 13 33 ing, CNRS UMR 7635, CS 10207 rue Claude Daunesse, 06904 Sophia Antipolis Cedex, France, 14 15 34 [email protected] 16 17 35 18 19 36 Jens Biele, Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Linder Höhe, Cologne, 51147, Ger- 20

21 37 many, [email protected] 22 23 38 24 25 39 Simon Tardivel, CNES, BPI 2532, Laplace 116B, 18 avenue Edouard´ Belin, 31401 Toulouse Cedex 9, 26 27 28 40 France, [email protected] 29 30 41 31 32 42 Olivier Groussin, Aix Marseille Universit´e, CNRS, CNES, Laboratoire d’Astrophysique de Marseille, 33 34 43 Marseille, France, [email protected] 35 36 44 37 38 45 Laurent Jorda, Aix Marseille Universit´e, CNRS, CNES, Laboratoire d’Astrophysique de Marseille, Mar- 39

40 46 seille, France, [email protected] 41 42 47 43 44 48 Joerg Knollenberg, Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Planeten- 45 46 47 49 forschungn Rutherfordstrasse 2, 12489 Berlin, Germany, [email protected] 48 49 50 50 51 51 Jan Thimo Grundmann, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Institute of Space 52 53 52 Systemsn Robert-Hooke-Strasse 7, D-28359 Bremen, Germany, [email protected] 54 55 53 56 57 54 Denis Arrat, CNES, BPI 2532, Laplace 116B, 18 avenue Edouard´ Belin, 31401 Toulouse Cedex 9, France, 58

59 55 [email protected] 60

61 56 62 63 64 2 65 57 Gabriel Pont, CNES, BPI 2532, Laplace 116B, 18 avenue Edouard´ Belin, 31401 Toulouse Cedex 9, France, 1 2 58 [email protected] 3 4 59 5 6 60 Stephane Mary, Directorate for Orbital Systems / Science Project Department, 18 avenue Edouard Belin, 7 8 9 61 31401 Toulouse Cedex 9, France, [email protected] 10 11 62 12 13 63 Markus Grubestein, Deutsches Zentrum f¨ur Luft- und Raumfahrt e.V. (DLR), 82234 Oberpfaﬀenhofen, 14 15 64 Germany, [email protected] 16 17 65 18 19 66 Hirdy Miyamoto, Department of Systems Innovation, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 20

21 67 Tokyo 113-8656, Japan, [email protected] 22 23 68 24 25 69 Tomoki Nakamura, Laboratory for Early Solar System Evolution, Department of Earth Science, Graduate 26 27 28 70 School of Science, Tohoku University, Aoba, Sendai, Miyagi 980-8578, Japan, [email protected] 29 30 71 31 32 72 Koji Wada, Planetary Exploration Research Center (PERC), Chiba Institute of Technology (Chitech), 33 34 73 Tsudanuma 2-17-1, Narashino, Chiba 275-0016, Japan, [email protected] 35 36 74 37 38 75 Kent Yoshikawa, Research and Development Directorate, Japan Aerospace Exploration Agency, Sagami- 39

40 76 hara 252-5210, Japan, yoshikawa.kento@jaxa.jp 41 42 77 43 44 78 Kiyoshi Kuramoto, Faculty of Science, Hokkaido University Kita-10 Nishi-8, Kita-ku, Sapporo 060-0810, 45 46 47 79 JAPAN, [email protected] 48 49 80 50 51 81 Joint ﬁrst authors: P. Michel and S. Ulamec contributed equally to this work 52 53 82 54 ∗ 55 83 Corresponding author: [email protected] 56 57 58 59 60 61 62 84 Preprint submitted to Earth, Planets and Space on January 1, 2021 63 64 3 65 85 Abstract 1 2 86 The Japanese MMX sample return mission to Phobos by JAXA will carry a Rover developed by CNES 3 4 87 and DLR that will be deployed on Phobos to perform in-situ analysis of the Martian moon’s surface 5 6 88 properties. Past images of the surface of Phobos show that it is covered by a layer of regolith. However, 7 8 9 89 the mechanical and compositional properties of this regolith are poorly constrained. In particular 10 11 90 nothing is known regarding the particle sizes, their chemical composition, the packing density of the 12 13 91 regolith as well as other frictional parameters and surface dynamics from current remote images. 14 15 92 Understanding the properties and dynamics of the regolith in the low-gravity environment of Phobos is 16 17 93 important to trace back its history and surface evolution. Moreover, this information is also important 18 19 94 to support the interpretation of data obtained by instruments onboard the main spacecraft and to 20

21 95 minimize the risks involved in the sampling by the spacecraft. The instruments onboard the Rover are 22 23 96 an infrared radiometer (miniRad), a Raman spectrometer (RAX), two cameras looking forwards for 24 25 97 navigation and science purposes (NavCams), and two cameras observing the flow of regolith around the 26 27 28 98 rover wheels (WheelCams). The Rover will be deployed before the sampling of Phobos’ surface by MMX 29 30 99 spacecraft and will be the first rover driving on a Martian moon and in a low-gravity environment. 31 32 33 100 Keywords 34 35 101 Camera, Numerical Modeling, Phobos, Radiometer, Raman Spectrometer, Regolith, Regolith Dynamics, 36 37 102 Thermal Inertia, Rover 38 39 40 41 42 43 44 45 103 Introduction 46 47 104 The MMX Rover is a contribution by the Centre National d’Etudes Spatiales (CNES) and the German 48 49 105 Aerospace Center (DLR) to the Martian Moons eXploration (MMX) mission by the Japan Aerospace 50 51 106 Agency, JAXA, to the Martian moons Phobos and Deimos (Kuramoto et al. 2017; Kawakatsu et al. 52 53 54 107 2019). It will be delivered to the surface of Phobos to perform in-situ science but also to serve as a 55 56 108 scout, preparing the landing of the main spacecraft. The Rover is planned to be released from the mother 57 58 109 spacecraft at an altitude of less than 100 m (the current baseline foresees 45 m), ballistically descend 59 60 110 to the surface of Phobos and come to rest in an arbitrary attitude after several bounces. After this it 61 62 63 64 4 65 111 will upright itself and deploy its solar panels. In addition to its scientific objectives, as described in 1 2 112 the following section, the MMX Rover will demonstrate locomotion using on wheels in a low gravity 3 4 113 environment. The distance the rover can move on the surface of Phobos will strongly depend on the 5 6 114 actual terrain that is not yet known, thus no strict requirements have been set (such as described in, e.g., 7 8 9 115 Lorenz 2020). During the rover mission a total distance from a few meters to hundreds of meters may 10 11 116 be covered. All telemetry and commands will be sent via the MMX mother spacecraft, acting as a relay. 12 13 117 More details on the rover system are given by Ulamec et al. (2019). 14 15 16 17 118 General Science Objectives 18 19 119 The scientific objectives of the MMX rover are defined in line with those of the overall MMX mission, 20

21 120 complementing the science which can be performed with the instruments on board the main spacecraft 22 23 121 or the returned samples. 24 25 122 These instruments are two navigations cameras (called NavCams), two cameras that will observe the 26 27 28 123 regolith flow on the back and front wheels (called WheelCams), a Raman spectrometer (called RAX) 29 30 124 and a miniaturized radiometer (called miniRad). Figure 1 shows the rover deployed configuration and 31 32 125 its internal compartment, while Fig. 2 shows its on-surface configuration. 33 34 126 The data provided by the rover instrument suite are extremely valuable for the communities interested 35 36 127 in regolith dynamics in the low gravity environment of Phobos, in surface processes, in the formation, 37 38 128 geological history and composition of Phobos, and in its thermal properties. The data set that will be 39

40 129 obtained in-situ is of high value for the interpretation of data obtained remotely by the spacecraft. It 41 42 130 will add ground truth, and provide a geological context to the samples that will be returned to Earth in 43 44 131 order to clarify the origin and history of Phobos. 45 46 47 132 The Rover will perform: 48 • 49 133 Close-up and high resolution imaging of the surface terrain. 50 51 134 • Regolith science (e.g. dynamics, mechanical properties like surface strength, cohesion; geometrical 52 53 135 properties like grain size distribution, porosity). 54 55 136 • Measurements of the mineralogical composition of the surface material (by Raman spectroscopy). 56 57 137 • Determination of the thermal properties of the surface material (surface temperature, emissivity, 58

59 138 thermal conductivity, layering). 60 61 139 The measurements by the MMX rover will allow determination of the heterogeneity of the surface material 62 63 64 5 65 140 and thus will support the MMX landing and sampling. Furthermore, the characterization of the regolith 1 2 141 properties shall considerably reduce the risk of the landing (and sampling) of the main spacecraft, as the 3 4 142 rover will offer the only direct measurements of Phobos’ surface response to an external action. 5 6 7 8 9 143 Science with the Raman Spectrometer (RAX) 10 11 144 In line with the top-level science objectives of the MMX mission as defined by JAXA, namely gaining 12 13 145 knowledge about the origin, evolution, and formation of Solar System bodies, Raman spectroscopy will be 14 15 146 used to provide in-situ information about Phobos’ geochemical composition. For this a Raman spectrom- 16 17 147 eter onboard the rover will investigate its surface mineralogy in the µm scale. This Raman spectrometer 18 19 148 for MMX (RAX) (Fig. 3) is a compact, low-mass instrument with a volume of approximately 81×98×125 20 3 21 149 mm and a mass of less than 1.4 kg developed by DLR, INTA/UVA and JAXA/UTOPS/Rikkyo (Cho 22 23 150 et al. 2020, , this issue). It is designed to withstand the harsh conditions on Phobos and will be the first 24 25 151 Raman spectrometer on an airless body. The measurements performed with RAX include the identifica- 26 27 28 152 tion of minerals on various points on the surface of Phobos, validated by comparison with experiments in 29 30 153 laboratories on Earth and spectral laboratory reference data bases. The acquired data will support and 31 32 154 complement the orbiter spectroscopic measurements and the measurements performed on the returned 33 34 155 samples as ground truth. Furthermore, the RAX data will be compared with the results obtained with 35 36 156 the Raman spectrometer RLS during the ExoMars2022 mission on the surface of Mars. All this taken 37 38 157 together, it helps to better understand the origin of its moons. 39 40 41 42 158 Science with the miniaturized radiometer (miniRAD) 43 44 159 The miniaturized Radiometer (miniRAD) aims at investigating the surface temperature of Phobos by 45 46 47 160 measuring the radiative flux emitted in the thermal infrared wavelength range using thermopile sensors 48 49 161 (Kessler et al. 2005). The instrument, which will be mounted in the front compartment of the rover, has 50 51 162 strong heritage from the Rosetta MUPUS thermal mapper (Spohn et al. 2007), the MASCOT radiometer 52 53 163 (Grott et al. 2017), and the InSight radiometer (Spohn et al. 2018; Müller et al. 2020). The six miniRAD 54 ◦ 55 164 sensors have a field of view of 45 and will observe a spot at a distance of ∼25 to ∼150 cm in front of 56 57 165 the rover, which will be located within the field of view of the stereo navigation cameras (navCAMs, see 58

59 166 Sec. ). In this way, geological context for the miniRAD observations will be provided along with a digital 60 61 167 terrain model of the scene. 62 63 64 6 65 168 The surface temperatures T on Phobos are governed by the surface energy balance, which is driven by 1 2 169 insolation S and given by 3 4 4 − π ∂T 5 σBεT = (1 A)S + Γ ′ (1) rP ∂z ′ 6 z =0

7 8 170 where σB is the Stefan-Boltzmann constant, ε is surface emissivity, A is bond albedo, P is Phobos’ 9 ′ 10 171 rotation period, and z = z/d is depth z normalized to the skin depth d = kP/ρcpπ. Here, ρ is the 11 p 12 172 material’s bulk density, cp is heat capacity, and k is thermal conductivity. In Eq. 1, the thermal inertia 13 14 15 Γ= kρcp (2) 16 p 17 173 is the material parameter governing the surface’s temperature response to heating, where low values 18 19 174 of Γ correspond to fast changes and vice versa. Therefore, given surface emissivity as well as surface 20 21 22 175 temperature, the material’s thermophysical parameters can be estimated (Hamm et al. 2018). 23 24 176 Phobos’ thermal inertia was first estimated from Viking orbiter data (Lunine et al. 1982), and values 25 −2 −1 −1/2 26 177 between 25 and 85 J m K s were determined. Interpretation of Phobos 2 data yielded similarly 27 −2 −1 −1/2 28 178 low results in the 33 to 83 J m K s range (Ksanfomality et al. 1989), and estimates taking 29 −2 −1 −1/2 30 179 surface roughness into account derived thermal inertias between 20 and 40 J m K s using the 31 32 180 same data set (Kuehrt and Giese 1989; Kuehrt et al. 1992). Spatially resolved thermal inertia maps were 33 34 181 first derived from Mars Global Surveyor thermal emission spectrometer (TES) measurements (Smith et 35 36 −2 −1 −1/2 182 al. 2018), and a globally averaged thermal inertia of 70 J m K s was obtained. There is some 37 38 −2 −1 −1/2 183 evidence for regions with thermal inertias larger than 100 J m K s in the TES data (Smith et al. 39 40 41 184 2018), and some regions with anomalously high thermal inertia were also reported based on Phobos 2 data 42 43 185 (Ksanfomality et al. 1989; Kuzmin and Zabalueva 2003), indicating at least some spatial heterogeneity 44 45 186 with respect to surface thermophysical properties and potentially rock abundance. Furthermore, data 46 47 187 provided by the Mars Odyssey THEMIS instrument (Bandfield et al. 2018) seems to be best compatible 48 49 188 with a layered regolith structure, and models considering a several centimeter thick cover of fine regolith 50 −2 −1 −1/2 −2 −1 51 189 with thermal inertia of 50 J m K s above a consolidated layer with inertias of 1000 J m K 52 −1/2 53 190 s best reproduce the observations. 54 55 191 The above range of thermal inertias corresponds to thermal conductivities between 0.00076 and 0.023 W 56 57 −1 −1 192 m K (Kuzmin and Zabalueva 2003), which can be compared to estimates obtained for other small 58 59 60 193 bodies. Fig. 4 shows thermal conductivity as a function of temperature for Phobos as well as C-class 61 62 194 asteroids, S-class asteroids, average near Earth asteroids, and comets. The thermal conductivity of the 63 64 7 65 195 lunar regolith is shown as a reference. While surface thermal conductivity on most minor bodies exceeds 1 2 −1 −1 −1 −1 196 0.025 W m K , the current best estimate for Phobos is only 0.007 W m K and thus similar to 3 4 −1 −1 197 the lunar value of 0.003 W m K . This has generally been interpreted in terms of a surface cover of 5 6 198 fine grained regolith with average particle diameters in the few millimeter range (Gundlach and Blum 7 8 9 199 2013). Furthermore, the reported low thermal conductivity indicates a low surface rock abundance in the 10 11 200 few percent range. 12 13 201 The interpretation of the available thermal infrared data for Phobos is complicated by the fact that 14 15 202 to date, all available data-sets cover only a limited range of local times. However, the influence of, 16 17 203 e.g., surface roughness (Kuehrt et al. 1992) or layering is best studied considering the entire diurnal 18 19 204 temperature curve. Surface roughness strongly affects thermal emission on airless bodies (Kuehrt et al. 20

21 205 1992; Davidsson et al. 2015), and its effect on emitted flux is shown in Fig. 5, where the ratio of the 22 23 206 flux emitted by a rough surface to that emitted by a flat Lambertian surface is shown as a function of 24 25 207 solar zenith angle. The employed roughness model (Giese and Kuehrt 1990; Kuehrt et al. 1992; Lagerros 26 27 28 208 1996) considers a surface covered by hemispherical craters, a crater density of 50%, a bond albedo of 0.02, 29 30 209 an emissivity of 0.95, and a heliocentric distance of 2 AU. As is evident from the figure, roughness can 31 32 210 dramatically change the flux received by the instrument when compared to a flat surface, and this effect 33 34 211 is most pronounced at short wavelengths under low sun conditions. Therefore, observing temperatures 35 36 212 for a full day-night cycle over the entire range of solar incidence angles provides data that can help to 37 38 213 resolve some of the inherent ambiguities when interpreting received flux in terms of surface temperatures. 39

40 214 Furthermore, measurements at diﬀerent wavelengths can help to disentangle surface roughness from 41 42 215 thermal inertia. 43 44 216 The sensing depth of thermal infrared observations is of the order of a few diurnal skin depths d. The 45 46 47 217 latter is expected to be close to 5 mm for Phobos’ regolith and of the order of a few centimeters for typical 48 49 218 boulders. Therefore, shallow regolith layering or the presence of a thin veneer of low thermal inertia dust 50 51 219 covering bedrock or boulders should be detectable by thermal infrared measurements. Layering has a 52 53 220 pronounced eﬀect on surface temperatures (Biele et al. 2019; Grott et al. 2019), and cooling rates after 54 55 221 sunset are particularly sensitive. Therefore, data covering full diurnal temperature cycles can be used to 56 57 222 constrain the presence or absence of layering, as has been done for a boulder on asteroid Ryugu during 58

59 223 its visit by the JAXA Hayabusa2 spacecraft using the lander MASCOT radiometer data (Grott et al. 60 61 224 2019). 62 63 64 8 65 225 The miniRAD instrument onboard the MMX rover will observe the surface of Phobos in 6 distinct wave- 1 2 226 length bands and investigate different geological units along the rover’s traverse. Surface temperatures of 3 4 227 fine grained regolith as well as boulders will be determined for full diurnal cycles, thus enabling interpre- 5 6 228 tation of the data in terms of thermophysical properties, roughness, and layering. For granular material, 7 8 9 229 miniRAD will determine regolith thermal conductivity, porosity, and particle size (Ogawa et al. 2019), 10 11 230 while for boulders, thermal conductivity as well as porosity can be determined. The miniRAD data will 12 13 231 be diagnostic for determining the potential presence of thin dust covers on boulders, and the influence of 14 15 232 surface roughness will be quantified by observing the same target in different wavelength bands. In this 16 17 233 way, material properties can be determined and directly compared to those of other small bodies and 18 19 234 known meteorites (Flynn et al. 2018), shedding light on the moon’s formation and evolution processes. 20 21 22 23 235 Science with the Navigation Cameras (NavCams) 24 25 236 The NavCams are a set of stereo cameras (two cameras, aligned on a bench) observing the landscape in 26 27 28 237 front of the rover (Fig. 6). As their name indicates, their purpose is to allow both for the navigation of 29 30 238 the rover and its progression, autonomously or commanded from ground, on the possibly rough terrain 31 32 239 of Phobos and performing unprecedented science at the surface of Phobos. 33 34 240 The cameras are based on a microcamera cube CMV-4000 developed by CNES and 3DPLUS company. 35 36 241 The image sensor consists of a 2048 by 2048 array (4 Mpixel), with each pixel having a 5.5µm pitch. It is 37 38 242 based on a pinned photodiode to reach low noise and high electro-optic performances. For the NavCams, 39

40 243 this microcamera cube is equipped with a color image sensor (Bayer filter, i.e. forming a RGGB 2x2 41 42 ◦ ◦ 244 mosaic that repeats across the detector). The optics lead to a field-of-view of 118 in diagonal and 83 43 44 245 edge-to-edge, and a depth-of-field allowing to acquire images of the surface from 35 cm up to infinity. At 45 46 ∼ 47 246 1 m distance the spatial resolution is about 1 mm per pixel. 48 49 247 Beyond the identification of areas of interests, the NavCam images will allow the characterization of the 50 51 248 surface topography and morphologies at high spatial resolution as well as the determination of the spatial 52 53 249 distribution of the blue and red materials already detected at a lower spatial resolution on Phobos (e.g., 54 55 250 Thomas et al. 2011; Pieters et al. 2014). To fulfil these scientific objectives, we will rely on the generation 56 57 251 of 1) geo-referenced digital terrain models (DTMs), 2) albedo maps, and 3) low resolution spectral maps. 58

59 252 In particular, the NavCams’ observations will allow progress to be made in our understanding of the 60 61 253 origin of the blue and red materials. As of today, no simple spatial distribution nor stratigraphic relation 62 63 64 9 65 254 between these materials can be discerned (Pieters et al. 2014). There is also no apparent color-age relation 1 2 255 for small craters: fresh (recent) craters expose either type of material at diﬀerent locations (Pieters et 3 4 256 al. 2014). Given the observed spatial relationships, it is currently diﬃcult to formulate a single model 5 6 257 through which the red unit is largely a depositional unit or is derived from the blue unit by some form 7 8 9 258 of space weathering. 10 11 259 In addition, the local high resolution DTMs will be geo-referenced to the global DTM of Phobos 12 13 260 reconstructed from the orbiter camera (TENGOO). The unprecedented resolution of the local DTMs 14 15 261 will allow us to identify and characterize small scale topographic features such as grains, boulders and 16 17 262 cracks. These DTMs will allow the size distribution of the grains to be constrained down to 1 mm and 18 19 263 tentatively allow monitoring any regolith movement and albedo variation on short timescales. They will 20

21 264 be a key complement to the geomorphologic analyses performed with the orbiter camera observations for 22 23 265 the whole surface and will allow us to reﬁne our understanding of the overall geological history of Phobos. 24 25 26 27 28 266 Science with the Wheel Cameras (WheelCams) 29 30 267 The WheelCams are a set of two cameras placed on the underside of the rover and each aimed at a 31 32 268 diﬀerent wheel (Fig. 7). Their primary purpose is to observe the wheels and the behavior of the regolith 33 34 269 around the wheels as the rover is advancing on Phobos, providing unique information on the dynamics 35 36 270 of the regolith in the low-gravity environment of Phobos. Their secondary purpose is to provide colour 37 38 271 images at very high resolution of the Phobos soil. 39

40 272 The cameras are based on the same microcamera cube as the NavCams (see previous section). However, 41 42 ◦ 273 the detector is panchromatic (no colour filter). The optics provide a field of view of 32.5 , a best focus 43 44 274 distance of 35 cm and a field depth of 10 cm. This gives a pixel resolution of approximately 70 µm at 45 46 47 275 the center of the image. 48 49 276 In order to illuminate the scene, which is almost always in the shadow of the rover body and solar panels, 50 51 277 they are equipped with LEDs. Some are “high power” (0.5 W) white LEDs to be used while driving, while 52 53 278 others are colour LEDs of specific bandwidths to allow for multispectral imaging. These colour LEDs are 54 55 279 from the Euclid mission (ESA): the L-590, the L-720 and the EOLD-880 at respectively 590 nm, 720 nm 56 57 280 and 880 nm (Boutillier et al. 2014). 58

59 281 The cameras can be used with the white LED while the rover is driving (typical image frequency will be 60 61 282 about one picture every second for a motion of about 1 mm/s), or at night with the color LEDs and with 62 63 64 10 65 283 longer exposure times. Because of the huge data volumes produced by the image sequences, they are 1 2 284 binned down to 1024 by 1024 images and cropped to retain only the most important part of the picture. 3 4 285 Temporal compression if the image sequences is also considered, but not conﬁrmed at this stage. On the 5 6 286 other hand, the detailed night images with the color LEDs are transmitted with lossless compression (no 7 8 9 287 binning or cropping). 10 11 288 The physical properties of Phobos’ surface are closely linked to the history and origin of the body. Such 12 13 289 information also has important implications for spacecraft - surface interactions such as the landing of the 14 15 290 main MMX spacecraft and the surface sampling. Given that remote observations can often lead to very 16 17 291 diﬀerent interpretations on surface and internal properties, the only way to truly probe the mechanical 18 19 292 and physical properties is to directly interact with the surface material. By observing the surface and the 20

21 293 interactions between the rover wheels and the regolith, the WheelCams will study the mechanical and 22 23 294 dynamical properties of Phobos’ regolith. 24 25 295 The WheelCams will be used to characterise the general grain properties of Phobos’ regolith. Speciﬁcally, 26 27 28 296 the high resolution WheelCam images will allow the regolith particles to be identiﬁed down to particle 29 30 297 sizes of approximately 200 µm. Combining this information with local high resolution DTMs from the 31 32 298 NavCams, and images and global DTMs from the main MMX spacecraft will provide the particle size 33 34 299 distribution, spanning many more orders of magnitude than previous studies of Phobos (Thomas et al. 35 36 300 2000). The slope of the particle size distribution can indicate how much processing (impacting, breaking, 37 38 301 size sorting, transporting) Phobos’ regolith has experienced. The grain morphologies (sphericity and 39

40 302 angularity) will also be investigated (for grains > 1 mm) using the WheelCam images. 41 42 303 The rover wheel – regolith interactions will also be investigated in detail; the WheelCams will determine 43 44 304 the depth of the wheel sinkage, which is closely linked to the load bearing strength and friction angle 45 46 47 305 of the regolith (Sullivan et al. 2006). Observations of talus in the rover tracks (Sullivan et al. 2006) 48 49 306 and tailings behind the wheels provide measurements of the angle of repose, and undisturbed trench 50 51 307 walls provide a lower limit to the regolith cohesion (Sullivan et al. 2011). In addition, measurement of 52 53 308 traction and slippage (e.g. Maimone et al. 2007; Reina et al. 2006) will provide shearing characteristics of 54 55 309 the regolith. These numerous observations will be compiled in order to characterise the bulk properties 56 57 310 of the regolith, and to improve our understanding of granular ﬂow on Phobos and in reduced-gravity 58

59 311 environments in general, with profound implications on Phobos’ surface history. 60 61 62 63 64 11 65 312 Numerical modeling for supporting rover dynamics and interpreting regolith properties 1 2 313 The instruments onboard the MMX rover will provide substantial information on the small scale topo- 3 4 314 graphic features and grain properties of Phobos’ surface. The dynamical behaviours of regolith materials 5 6 315 both in quasi-static and flow regimes will be intensively characterised by the WheelCams. However, as 7 8 9 316 the first rover rolling in a milli-gravity environment, the established knowledge about rover dynamics and 10 11 317 regolith compliance from the Moon and Mars exploration and Earth laboratory experiments would not be 12 13 318 applicable to interpret this information. Recent small body missions (i.e., Hayabusa2 and OSIRIS-REx) 14 15 319 have showed that the responses of these airless, low-gravity small-body surfaces to robotic maneuvers 16 17 320 are significantly different from those observed in an Earth-gravity environment (Arakawa et al. 2020; 18 19 321 Bierhaus et al. 2020). 20

21 322 As an eﬀective test bed for various physical properties and dynamical processes, numerical modeling is 22 23 323 crucial to the design of the locomotion system and potentially other platform systems. Simulations are also 24 25 324 required to help with the processing of the WheelCam images and determine the mechanical properties 26 27 28 325 of the regolith. The calibrated material model and parameters can be further used to simulate the 29 30 326 geophysical evolution of Phobos over its lifetime. Combined with the regolith mineralogical composition 31 32 327 and thermal properties measured by the RAX and miniRad instruments,respectively, numerical modeling 33 34 328 will help to constrain the origin and evolution of Phobos. 35 36 329 To fulﬁll the above science objectives, at least two complementary numerical approaches, with discrete 37 38 330 and continuum treatments respectively, will be used to study the rover and regolith dynamics. 39

40 331 Soft-sphere Discrete Element Method (SSDEM) 41 42 332 The soft-sphere discrete element method (SSDEM) is a highly accurate but costly option for studying 43 44 333 rover interactions with granular surfaces. In this method, the overall behavior of the system is determined 45 46 47 334 by calculating the contact forces acting on each grain in a regolith bed and then advancing the system 48 49 335 accordingly. Contacts are evaluated at small time intervals, where the size of the time-step is dependent 50 51 336 on the properties of the grains. In general, stiffer surface materials will result in smaller time-steps and 52 53 337 longer processing times. A key benefit of SSDEM is that this method effectively captures the influence 54 55 338 of gravity and cohesion on granular flows without relying on empirical or semi-empirical relationships. 56 57 339 SSDEM has proven to be an effective tool for advancing research related to the formation and evolution 58

59 340 of small bodies (Sanchez and Scheeres 2014; Zhang and Lin 2020; Michel et al. 2020). This method has 60 61 341 also been used to assess the performance of planetary rovers, though most commonly for the gravity 62 63 64 12 65 342 environments found on the moon and Mars (Nakashima et al. 2007; Johnson et al. 2015). Currently, 1 2 343 DLR is using DEM combined with machine learning to assist with the design and optimization of the 3 4 344 MMX rover wheel for Phobos-like surface conditions (Buchele and Lichtenheldt 2020). 5 6 345 A signiﬁcant challenge associated with DEM is selecting the appropriate simulation parameters when 7 8 9 346 the material properties of the surface are largely unknown. For the rover studies, simulations can be 10 11 347 conducted for the entire range of soil cases presented in the previous section presenting the soil and grain 12 13 348 mechanical environment. Then, the results can be used to create a map between observable outcomes 14 15 349 like trench shape, wheel sinkage, and wheel slip, and important material properties like those discussed 16 17 350 in the section presenting the science of the Wheelcams, such as cohesion and internal friction. 18 19 351 Fig. 8 provides an example of a typical simulation with a simpliﬁed rover wheel and a bed of large, 20

21 352 spherical particles. In addition to wheel sinkage, the grain-scale resolution of DEM allows us to observe 22 23 353 the shear-band created by the granular flow under the wheel. 24 25 354 Continuum method 26 27 28 355 A continuum description of dense granular materials can be used as a fast and coarse approach to model 29 30 356 the rheology of granular beds. In this type of description, local particle velocities are averaged, resulting 31 32 357 in a continuous velocity field (Da Cruz et al. 2005). Additionally, forces between particles are averaged 33 34 358 up to viscous stress and pressure fields, similar to the Navier-Stokes equation for viscous fluids. 35 36 359 A first version of a continuous model for dense granular flows was proposed by Jop et al. (2006), 37 38 360 based on the expression of an apparent (in the macroscopic sense) friction coefficient µ. This model 39

40 361 makes it possible to reproduce the viscoplastic effects and the dependence on normal stresses observed 41 42 362 experimentally and numerically using discrete numerical simulations (Da Cruz et al. 2005), such as the 43 44 363 existence of a flow threshold, the dependence of µ on speed, pressure, size and density of grains. In this 45 46 47 364 model, the apparent friction is an increasing function of a single parameter I, called an inertial number, 48 0.5 49 365 defined by I =γd/ ˙ (P/ρ) , whereγ ˙ , d, P and ρ are, respectively, the second invariant of the strain 50 51 366 rate tensor, the mean particle diameter, the confining (macroscopic) pressure and the grain density. This 52 53 367 parameter measures the relative contribution of the inertial (or kinetic) pressure to the confining (static) 54 55 368 pressure. 56 57 369 This so-called µ(I) model has been successfully applied to predict rheometric shear flows, stationary one- 58

59 370 and two-dimensionnal free surface flows (GDR MiDi group 2004) as well as three-dimensional transient 60 61 371 free surface flows (Valette et al. 2019), using numerical simulations. 62 63 64 13 65 372 Recent extensions of the µ(I) model, such as the one proposed by Vo et al. (2020), make it possible 1 2 373 to take into account in the same formalism both cohesive and viscous effects. In this continuous model 3 4 374 again, the number of parameters is restricted, and will allow us to quickly explore several conditions for 5 6 375 rover interactions with the granular bed. Subsequent inverse mapping of continuum to SSDEM models 7 8 9 376 parameters can then accelerate the fine processing of WheelCam images using SSDEM. 10 11 12 13 377 Conclusions and Outlook 14 15 378 The MMX mission will provide the first detailed information on Phobos, and the first sample of a martian 16 17 379 moon for analysis in laboratories on Earth. The rover that the spacecraft will deploy on Phobos’ surface 18 19 380 will obtain the first in-situ information on the compositional and physical properties of the surface of 20

21 381 this moon as well as on the dynamics of regolith in the corresponding gravitational environment. Direct 22 23 382 measurements of the surface response to an external action, such as the rolling of rover’s wheels, are 24 25 383 of unique value both for science and technical purposes. Comparison between microscale properties 26 27 28 384 measured by the rover and macroscale ones measured by the instruments onboard the spacecraft, as well 29 30 385 as the sample analyses will be of high value and will allow the maximum science return of the mission to 31 32 386 be achieved. 33 34 387 After finishing Phase B in 2020 the rover will go through a full qualification program. The flight model 35 36 388 will be delivered to Japan in 2023, to be integrated to the main MMX spacecraft where a combined 37 38 389 testing program is foreseen. The MMX mission is planned to be launched in 2024. After arrival at 39

40 390 Phobos, remote investigations will start, which will include landing- and sampling site selections. The 41 42 391 rover will then be delivered to the surface of Phobos in 2026 or early 2027 and is planned to operate on 43 44 392 Phobos for at least 100 days. Telemetry and Commands will be relayed via the mother spacecraft. There 45 46 47 393 are dedicated Rover Operations centers at DLR in Cologne/Germany and at CNES in Toulouse/France. 48 49 394 MMX will leave Mars orbit in 2028 and return to Earth in August 2029 (Kawakatsu et al. 2019) with 50 51 395 Phobos samples. 52 53 54 55 396 Availability of data and materials 56 57 397 Not applicable. 58 59 60 61 62 63 64 14 65 398 Competing interests 1 2 399 Not applicable 3 4 5 6 400 Funding 7 8 9 401 This work benefits from funding by CNES and DLR. CS acknowledges PhD thesis funding from ISAE- 10 11 402 SUPAERO and CNES. Y.Z. acknowledges funding from the UniversitéCôte d’Azur “Individual grants 12 13 403 for young researchers” program of IDEX JEDI. 14 15 16 17 404 Authors’ contributions 18 19 405 The authors wish it to be known that, in their opinion, the first two authors (PM and SU) should be 20

21 406 regarded as joint First Authors. 22 23 24 25 407 Acknowledgments 26 27 28 408 The rover on the MMX mission of JAXA is a CNES-DLR cooperation. The authors would like to 29 30 409 thank the whole MMX team at JAXA/ISAS for the unique opportunity to participate to this exciting 31 32 410 mission. 33 34 35 36 411 References 37 38 412 Arakawa M, Saiki T, Wada K, Ogawa K, Kadono T, Shirai K, et al. (2020) An artiﬁcial impact on the 39

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40 563 Ulamec S, Michel P and 54 colleagues (2019), A Rover for the MMX Mission to Phobos, 70th 41 42 564 International Astronautical Congress 43 44 565 Valette R, Riber S, Sardo L, Castellani R, Costes F, Vriend N, Hachem E (2019) Sensitivity to the 45 46 47 566 rheology and geometry of granular collapses by using the µ(I) rheology. Computers & Fluids 191: 48 49 567 104260 50 51 568 Vo TT, Nezamabadi S, Mutabaruka P, Delenne JY, Radjai F (2020) Additive rheology of complex 52 53 569 granular flows. Nature Communications 11: 1476 54 55 570 Zhang Y, Lin DNC (2020) Tidal fragmentation as the origin of 1I/2017 U1 (‘Oumuamua). Nature 56 57 571 Astronomy 4: 852-–860 58 59 60 61 62 63 64 20 65 1 Figure 1. Left: Rover in fully deployed configurations with positions of MiniRad, rear WheelCam 2 3 and NavCam stereo bench; right: internal compartment (Service Module – SEM) with position if 4 5 instruments and On Board Computer (OBC). Courtesy from CNES. 6 7 8 9 Figure 2. MMX rover with deployed wheels and solar panels in the on-surface configuration. Field of 10 11 12 Views of miniRAD and Wheelcams are indicated in yellow and red, respectively. Courtesy from CNES. 13 14 15 16 Figure 3. CAD model of RAX (Raman spectrometer for MMX). 17 18 19 20 Figure 4. Thermal conductivity as a function of temperature as derived for different small bodies. Data 21 22 for C-class asteroids Bennu (Emery et al. 2014; Dellagiustina et al. 2019; Rozitis et al. 2019) and Ryugu 23 24 (Müller et al. 2017; Hamm et al. 2020), for average near Earth asteroids (Delbo’ et al. 2007), for comets 25 26 9P/Tempel 1 (Groussin et al. 2013; Davidsson et al. 2009), 103P/Hartley (Groussin et al. 2013), and 27 28 67P/Churyumov-Gerasimenko (Spohn et al. 2015), for S-class asteroids Itokawa (Fujiwara et al. 2006) 29 30 and Eros (Lebofsky and Rieke 1979; Harris and Davies 1999) are shown together with the current best 31 32 estimate for Phobos (Kuzmin and Zabalueva 2003). For comparison, the thermal conductivity of the 33 34 lunar regolith (Hayne et al. 2017) is also given. 35 36 37 38 Figure 5. The ratio of flux emitted by a rough surface to that emitted by a flat Lambertian surface 39 40 as a function of solar zenith angle at three different wavelengths. Results are shown for an equatorial 41 42 ◦ 43 location and a south facing instrument, which observes the surface under an emission angle of 45 . 44 45 46 47 Figure 6. The navigation cameras. Left: CAD view; right: schematic view. 48 49 50 Figure 7. The wheel cameras in their pre-phase A design. Left: CAD view; right: schematic view. 51 52 53 54 Figure 8. Example SSDEM simulation of a simplified MMX rover wheel traversing a bed of 180,000 55 56 ± 57 cohesionless spherical grains. The wheel is 214 mm in diameter and the grains are 6 0.5 mm in 58 59 diameter. The simulation was conducted under Earth-gravity using Chrono (Sunday et al. 2020). The 60 61 grains are colored by velocity magnitude. 62 63 64 21 65 Figure 1a Figure 1b Figure 2 Figure 3 Figure 4

Ryugu Boulder Ryugu Global Bennu Average NEA CG (67P) Tempel 1 (9P) -1 Hartley 2 (103P) 10 Itokawa Phobos Lunar Regolith Eros

10-2 Thermal Conductivity [W/mK] Conductivity Thermal

100 150 200 250 300 350 Temperature [K] Figure 5 Figure 6 Figure 7 ω

Figure 8

0.08 m/s

0 Graphical Abstract (JPEG, PNG or SVG file - 920x300 pixels) Figures

Figure 1

Left: Rover in fully deployed conﬁgurations with positions of MiniRad, rear WheelCam and NavCam stereo bench; right: internal compartment (Service Module – SEM) with position if instruments and On Board Computer (OBC). Courtesy from CNES.

Figure 2

MMX rover with deployed wheels and solar panels in the on-surface conﬁguration. Field of Views of miniRAD and Wheelcams are indicated in yellow and red, respectively. Courtesy from CNES. Figure 3

CAD model of RAX (Raman spectrometer for MMX). Figure 4

Thermal conductivity as a function of temperature as derived for diﬀerent small bodies. Data for C-class asteroids Bennu (Emery et al. 2014; Dellagiustina et al. 2019; Rozitis et al. 2019) and Ryugu (Mu¨ller et al. 2017; Hamm et al. 2020), for average near Earth asteroids (Delbo’ et al. 2007), for comets 9P/Tempel 1 (Groussin et al. 2013; Davidsson et al. 2009), 103P/Hartley (Groussin et al. 2013), and 67P/Churyumov- Gerasimenko (Spohn et al. 2015), for S-class asteroids Itokawa (Fujiwara et al. 2006) and Eros (Lebofsky and Rieke 1979; Harris and Davies 1999) are shown together with the current best estimate for Phobos (Kuzmin and Zabalueva 2003). For comparison, the thermal conductivity of the lunar regolith (Hayne et al. 2017) is also given. Figure 5

The ratio of flux emitted by a rough surface to that emitted by a flat Lambertian surface as a function of solar zenith angle at three different wavelengths. Results are shown for an equatorial location and a south facing instrument, which observes the surface under an emission angle of 45฀. Figure 6

The navigation cameras. Left: CAD view; right: schematic view.

Figure 7

The wheel cameras in their pre-phase A design. Left: CAD view; right: schematic view. Figure 8

Example SSDEM simulation of a simpliﬁed MMX rover wheel traversing a bed of 180,000 cohesionless spherical grains. The wheel is 214 mm in diameter and the grains are 6 ± 0.5 mm in diameter. The simulation was conducted under Earth-gravity using Chrono (Sunday et al. 2020). The grains are colored by velocity magnitude.

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