TP15
This session welcomes submissions regarding the mission and its Pasteur Payload instruments, its scientific investigations, and on research activities pertinent to mission science objectives, including but not limited to: study of the Oxia Planum landing site and related locations, terrestrial analogue studies, astrobiological and sample analysis studies, and other relevant research topics. We also invite submissions regarding synergies between the ExoMars Rosalind Franklin Mission and other Mars missions and programmes.
Session assets
Finding signs of life elsewhere is one of the most important scientific objectives of our time.
From the very beginning in 2002, ExoMars was conceived to answer one question: Was there ever life on Mars? All project design decisions have focused and continue to centre on the achievement of this single scientific goal. This is particularly the case for the Rosalind Franklin rover [1]. Putting the science team in the best possible condition to search for physical and chemical biosignatures has led to:
- the need for a 2-m depth drill;
- the choice of payload instruments,
- the landing site requirements that led to selection of the Oxia Planum landing site, and
- the surface exploration strategy that guides how the rover and instruments are used together to achieve the mission objectives.
The Rosalind Franklin Mission (RFM) is a re-establishment of the ExoMars 2022 mission. In a new partnership with NASA, RFM is on schedule for launch in 2028. The ExoMars Science Working Team (ESWT), ExoMars project and industrial partners continue to be engaged in a programme of refurbishment of the rover and its instruments, and preservation of science team expertise and knowledge. The revised mission timeline provides great opportunity for further preparatory science, including of the Oxia Planum landing site and its analogues, by interpretation of orbital data, lab- and field-work, and numerical simulations.
The ExoMars Rover Science Operations Working Group (RSOWG), chartered in 2019 by the ESWT, is re-established for the 2028 mission and continues working at a sustainable pace to address specific needs serving to advance science readiness. The ‘Micro’ sub-group work on topics regarding the spatial scale of the samples that will be extracted from down to 2m by the rover’s drill, their analogues, and plans for their analyses, including by the three instruments in the rover’s Analytical Laboratory Drawer (ALD): MicrOmega [2], RLS [3] and MOMA [4]. Ongoing work regards a set of ‘Mission Reference Samples’ – a suite of analogue samples most relevant to the landing site and mission objectives, which are under characterization by ground models of these instruments. Members of the ‘Macro’ sub-group continue geological interpretation of the landing site, and recently have published the highest resolution geologic map of Oxia Planum, the culmination of a 4-year team effort [5]. In addition, a dedicated set of co-authors are preparing the Strategic Science Plan (SSP) of the mission, which traces mission science objectives, through to specific questions linked to hypotheses that are testable by the scientific instruments in the ‘Pasteur’ Payload.
A new European Entry Descent and Landing Module (EDLM) that is being developed will deliver Rosalind Franklin to Oxia Planum. Meanwhile, dedicated efforts are underway to maintain, and update as needed, systems at the Rover Operations Control Centre (ROCC - Turin, Italy). A continued plan of testing and simulations is planned in the coming years at ROCC, providing opportunities to exercise Science and Control Team processes. On the flight model of the Rosalind Franklin rover, instrument refurbishment activities are underway and a new infrared spectrometer ‘Enfys’ is in development to replace the analytical capabilities of the now disembarked ISEM instrument.
A special Science Knowledge Management Programme (SKP) has been set up and is now supporting key expertise within the science and instrument teams. SKP ensures that the valuable team knowledge and experience that was built in preparation for the 2022 mission opportunity [6] can be retained and developed.
This presentation will explain how ESA, with NASA partners, has reconfigured the Rosalind Franklin mission for a launch in 2028, present the current the level of advancement of the project, and will highlight the main science objectives and overall strategic plan for the mission.
Figure 1: Artist’s view of Rosalind Franklin approaching hydrothermal mound remains.
References
[1] Vago, J. L. et al. Habitability on Early Mars and the Search for Biosignatures with the ExoMars Rover. Astrobiology 17, 471–510 (2017).
[2] Bibring, J.-P., Hamm, V., Pilorget, C., Vago, J. L. & the MicrOmega Team. The MicrOmega Investigation Onboard ExoMars. Astrobiology 17, 621–626 (2017).
[3] Rull, F. et al. The Raman Laser Spectrometer for the ExoMars Rover Mission to Mars. Astrobiology 17, 627–654 (2017).
[4] Goesmann, F. et al. The Mars Organic Molecule Analyzer (MOMA) Instrument: Characterization of Organic Material in Martian Sediments. Astrobiology 17, 655–685 (2017).
[5] Fawdon, P. et al. ‘The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission’, Journal of Maps, 20(1) (2024). doi: 10.1080/17445647.2024.2302361.
[6] Sefton-Nash, E. et al. Science Operations Readiness of the ExoMars 2022 Rover Mission. in Lunar and Planetary Science Conference LPI Contributions 2678. Abs. 2109 (2022).
How to cite: Sefton-Nash, E. and Vago, J. L.: ExoMars/Rosalind Franklin Mission Update, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-856, https://doi.org/10.5194/epsc2024-856, 2024.
Oxia Planum is the selected landing site for the ExoMars Rosalind Franklin (RF) Mission, launching in 2028. The science objectives of the mission are to search for signs of life and to characterize the geochemical environment in the subsurface as a function of depth. RF will accomplish this with its ‘Pasteur’ suite of scientific instruments, and a drilling and sampling subsystem to retrieve samples for analysis from as deep as 2 m [1].
In preparation for this mission ESA, though the Rover Science Operations Working Group (RSOWG), has conducted a program of high resolution morphostratigraphic mapping and analysis to understand the geological significance of the landing site, to provide context for in-situ sample analysis and to serve as an input into strategic planning for rover operations. This effort: (i) has defined and described the geography of Oxia Planum as a framework for its exploration [2], (ii) has produced a geological map of the landing site [3], and (iii) in our ongoing work, is building a set of geological hypotheses that the RF rover can test during its nominal mission (in 2030-2031).
Figure. 1: The (a) location and (b) context of Oxia Planum, inc. the availability of CaSSIS data which has been critical to developing our regional understanding. (c) The geological map of the Oxia Planum landing site summarizing the major unit groups (see Figure 2).
Oxia Planum (Figure 1) preserves a record of the diverse geological process that formed and modified the landscape of western Arabia Terra throughout Mars’ geological history. Noachian Terrains contain extensive phyllosilicate–bearing materials in an environment of widespread aqueous alteration [4-7]. These deposits were subsequently added to (and modified by) fluvial activity and burial beneath regional layered terrain in the early Hesperian. They experienced further burial and erosion throughout the Amazonian [8-11]. Consequently, exploring the cross–section of strata exposed in Oxia Planum informs us about the paleoenvironmental conditions across a significant part of martian geological history (symbolized in Figure. 2). Furthermore, as Oxia is topographically open to the north, the processes recorded there probably reflect those occurring along the dichotomy boundary across the wider Chryse/Arabia region [4, 11- 15].
We present: (1) The high-resolution geological map of the landing site in Oxia Planum [3] and the data used to create it [2]. (2) An overview of hypotheses relevant to key events in Oxia Planum's geological history. (3) A discussion of how future RF observations will impact these questions and our wider understanding of Mars.
Figure 2: A summary of our current working hypotheses for the history of Oxia Planum visualized as an East to West schematic cross-section through the Oxia Basin. This connects the major geological units (Figure 1) to outstanding questions, the answer to which will tell us more about the overall geological evolution of Mars.
Acknowledgments: We thank the CaSSIS and HiRISE teams for ongoing data collection in support of the RF rover mission. PF thanks UK Space Agency (ST/W002736/1) and the ExoMars Science Knowledge Program (SKP) for funding.
References: [1] Vago et al. (2017) Astrobiology 17 (6–7), 471–510. [2] Fawdon, et al. (2021) J. Maps, 17:2, 621-637. [3] Fawdon et al. (2024) J. Maps 20(1). [4] Carter J. et al. (2015) Icarus 248, 373-382. [5] Quantin et al. (2021) Astrobiology 21:3, 345-366. [6] Mandon et al. (2021) Astrobiology 21:4, 464-480. [7] Brossier et al. (2022) Icarus 386. [8] McNeil et al. (2023) in LPSC 54 Abs.#1252. [9] Fawdon et al. (2022) JGR-Plan. 127, e2021JE007045. [10] Davis et al. (2023) EPSL 601, 117904. [11] Woodley et al. (2023) J. Maps, [12] Frueh et al. (2023) LPSC 54 Abs.#1440. [13] McNeil et al. 2022 JGR-Plan. 127, e2022JE007246. [14] Molina et al. (2017) Icarus 293 27-44. [15] Tornabene et al. (2023) LPSC 54 Abs.#2727
How to cite: Fawdon, P., Orgel, C., Adeli, S., Balme, M., Carter, J., Davis, J., Favaro, E., Frigeri, A., Grindrod, P., Harris, E., Hauber, E., Loizeau, D., McNeil, J., Mandon, L., quantin-nataf, C., Roberts, A., Thomas, N., Sefton-Nash, E., and Jago, J.: Scientific hypotheses for the ExoMars Rosalind franklin rover mission: a geological history of Oxia Planum., Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1080, https://doi.org/10.5194/epsc2024-1080, 2024.
Introduction: The deposits of ancient sediment fans on Mars can provide valuable insights into aqueous history, past climate conditions, and potential habitability. Fans are made of a suite of different sediment transport and depositional regimes including deltas, fluvial fans, alluvial fans, and submarine fans, all of which have been proposed to have been present on ancient Mars [1-3].
Oxia Planum, the landing site for the ESA’s ExoMars Rosalind Franklin rover mission, is hypothesized to have an extensive aqueous history likely recorded in its phyllosilicate-bearing units and complex sediment fan [4, 5]. The fan body originates from Coogoon Vallis in an area named Raetia Palus (Figure 1) [6]. Previous studies have conducted broad-scale investigations of this fan, proposing both fluvial fan and delta depositional models [5, 7-9]. To develop a more robust depositional model for the origin of the sediment fan, we conducted a photogeological investigation of sedimentary strata associated with this fan using orbital images and derived digital terrain models at a 1:1250 digital map scale.
Data: This investigation was undertaken using a newly created High-Resolution Imaging Science Experiment [HiRISE; 10] and HiRISE DTM mosaic with resolutions of 25 cm/pixel and 1 m/pixel, respectively. We also used Colour and Stereo Surface Imaging System [CaSSIS; 12] data products.
The sediment fan and associated units: The sediment fan consists of three key units with different textures and elevations: the ledge-forming unit (LF), overlain by the Medium-light Toned Smooth Unit (MltS), overlain by the Medium-light Toned Rough Unit (MltR) (Figure 2). Unit LF outcrops beneath the sediment fan as a light-toned ledge with curvilinear fractures (Figure 3). Unit MltS sharply overlies Unit LF with a smooth, medium-light toned, cratered surface. This unit exhibits three dark-toned and two lighter-toned layers, and at one location, inclined surfaces that dip to the northwest (Figure 4). A crater is impacted into this unit and filled with light-toned material, which is then unconformably overlain by Unit MltR. Unit MltR has an irregular surface texture characterised by abundant meter-scale blocks or boulders either on top or within the stratigraphy (Figure 4c).
The basement of Raetia Palus consists of four rock units: a raised linear feature-bearing unit (RL) and a light-toned, orthogonally fractured unit (LF), which is overlain by a dark-toned, pitted unit (P) and a sub-polygonally fractured unit (SF) (Figure 2). The sediment fan overlies Unit SF with a distinct bench-shaped contact (Figure 5). Units SF and P have a diffuse boundary, with Unit SF gradually losing fracture definition, gaining light-toned peaks, and pits infilled with dark-toned material that are characteristic of Unit P (Figure 5). Although the contact between Unit P and the sediment fan is often obscured by a mantling unit and was interpreted to onlap onto the sediment fan [5], we interpret that Unit P is a degraded version of Unit SF that may have been shielded from weathering by the overlying sediment fan.
An irregular ridge occurs within Unit MltR (Figure 2) which can be traced into a ridge extending northward for ~14,210 m, a possible reverse thrust fault identified elsewhere in Oxia Planum [11].
Geomorphology of the sediment fan: The sediment fan at Oxia Planum covers a surface area of 40.5 km2 and encompasses seven sedimentary bodies, labelled A through G (Figure 6; elevations -2965 m and -3039 m). Sediment bodies A through F are composed of the MltS unit. Sediment body A outcrops on the western side of the fan extending over the basin with finger-like extensions. Sediment body B partially overlies a crater within sediment-body A. Sediment body C, west of sediment body B, is intersected by wedge-shaped sediment body E containing inclined surfaces. Sediment bodies D and F form isolated, wide ribbon-like protrusions, and their relation to sediment bodies A through E is unknown.
Sediment body G overlies sediment bodies A through F and is composed of the MltR unit. The sediment body extends westward from the channel for ~5 km until terminating over the underlying lobes as an ~5 m thick irregular scarp with linear ridges.
Discussion and conclusions: The seven sediment bodies in Oxia Planum indicate evidence for at least seven different episodes of sediment deposition with two significant hiatuses from the presence of embedded craters between three sediment fan layers. We hypothesise that the sloping depositional surfaces within sediment body E are clinoform candidates which would indicate deposition into a shallow standing body of water. The distinction in shape and morphology of sediment body G, comprising unit MltR, and the hiatus represented by the infilled crater, may indicate a different depositional environment, potentially a fluvial fan or a delta top, overlying pre-existing fan deposits.
Our results also place the sediment fan in a stratigraphic context. We find that the fan post-dates Unit P and Unit SF - components of a dark-toned capping unit previously interpreted as the youngest rock unit in Oxia Planum [5] - but predates extensional faulting [11].
References: [1] Metz et al. (2009). [2] Fawdon et al. (2018). [3] Wilson et al. (2021). [4] Bowen et al. (2021). [5] Quantin-Nataf et al. (2021). [6] Fawdon et al. (2021). [7] Gary-Bicas et al. (2021). [8] Ivanov et al. (2020). [9] Fawdon et al. (2022). [10] McEwen et al. (2007). [11] Woodley et al. (2024). [12] Thomas et al. (2017).
Figures:
Figure 1: (a) CTX mosaic [6] of Oxia Planum (ExoMars 2028 landing ellipses, yellow; mapping extent, white); (b) HiRISE mosaic of Raetia Palus.
Figure 2: Photogeologic map, cross-section, and correlation of map units of Raetia Palus.
Figure 3: Unit LF: (a) context and a representative outcrop in (b) HiRISE and (c) CaSSIS.
Figure 4: Units MltS and MltR: with (a) context; (b) apparently steeply dipping surfaces of Unit MltS; (c) surficial boulders/blocks of Unit MltR; (d) gently-inclined light-and-dark-toned bands of Unit MltS.
Figure 5: Units SF and P: (a) context; the diffuse boundary in (b) HiRISE and (c) CaSSIS; (d) contact with Unit RL and the sediment fan in HiRISE.
Figure 6: Fan bodies against the orthorectified HiRISE mosaic with correlation of sediment bodies.
How to cite: Roberts, A., Gupta, S., Fawdon, P., Banham, S., Davis, J., and Harris, E.: Reconstructing Depositional Environments of the Sediment Fan in Oxia Planum, Mars, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1171, https://doi.org/10.5194/epsc2024-1171, 2024.
The Mars Organic Molecule Analyzer instrument (MOMA) is part of the ExoMars payload and aims to characterise the organic matter at the surface and subsurface of Mars. MOMA can be used under different configurations in order to achieve the study of the various samples that will be analysed by the rover. Crushed samples can be analysed by LD-MS, Pyr-GC-MS or wet chemistry – GC-MS. In this presentation we will focus on this last option. During the wet chemistry, the crushed samples will be put in an oven containing a derivatisant capsule. The chemical reagent inside the capsule enables a better volatilisation of our target molecules such as amino acids and carboxylic acids. Three different reagents are present in MOMA: DMF-DMA, TMAH and MTBSTFA. We focused most of our work on the later one. MTBSTFA is sealed in metallic capsules that open only at 221°C thanks to a eutectic. This is far from the temperature used in usual laboratories condition hence the need to adjust the time of reaction.
In order to optimise the characterisation of the organic matter with MOMA, each steps of sample preparation inside MOMA ovens must be optimised under the in-situ conditions: extraction and derivatisation. First, the thermal desorption of the organic molecules from analogues must be addressed. The thermal desorption was carried out at 200°C to stay under the eutectic but be high enough to be able to desorb the molecules from the mineral matrix. We need to desorb the molecules bonded to the mineral structure without degrading them. In order to optimise this desorption, Orbagnoux rock was used as analogue and showed good yield between 5 and 7 minutes of heating.
Only then, we focused on the derivatisation reaction. The first step is to make sure that the reagents will still be active after many years waiting for ExoMars flight to Mars. Experiments were carried out on control vials and capsules from 2015 for two derivatisants: DMF-DMA and MTBSTFA. Ancient reagent yields of functionalisation of amino acids were confronted to recent ones, showing comparable results. The effect of metal was effectuated by removing the capsule’s eutectic and draining the solvent with a syringe. The second step is to optimise the derivatisation of our target molecules. Three points were to be tackled: (i) the absence of DMF along with MTBSTFA in the capsule contrary to the common reaction in the laboratories, (ii) the temperature of derivatisation, (iii) the by-products appearing under these conditions. The first point revealed as expected a loss of signal for amino acids yet they can still be detected. The optimisation of the time of derivatisation leads to an optimum at 4 minutes, after that the amino acids tend to degrade due to the heat. Numerous by-products are observed, most of them are just partially derivatised amino acids or due to cyclisation through heating (Figure 1). The database associated to MOMA will be completed with these new compounds. Interestingly, depending on the initial mix we also observe the apparition of a-aminobutyric acid, a non proteinogenic amino acids that is commonly found in space objects such as meteorites. If our wet chemistry can induce the apparition of such compounds the conditions of apparition must be thoroughly understood to avoid misinterpretation of results on Mars. Linear and aromatic carboxylic acids showed good derivatisation under MOMA conditions.
Figure 1. Derivatisation with MTBSTFA of proline at 75°C and 220°C
The optimisation of the sample preparation inside MOMA ovens can be integrated in a lager vision of the process in term of heating time in the oven and therefore energy (Figure 2). It is important to have this general view in the perspective of keeping the maximum of energy to achieve the GC-MS run afterward. Indeed, molecules with higher masses will need a longer time of run so each minute will count.
Figure 2. Temperature profile of the MOMA oven during the different steps of sample preparation and after capsule opening.
How to cite: Azémard, C., Gonthier, R., Bouhier, B., Stalport, F., Lepot, K., and Cottin, H. and the MOMA team: In-situ sample preparation with MOMA instrument, derivatisation with MTBSTFA – ExoMars 2028 mission, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-183, https://doi.org/10.5194/epsc2024-183, 2024.
Rosalind Franklin will be the first Mars rover capable of drilling into the surface of Mars down to a depth of 2 m. Its drill system is designed to collect small core samples at depth and deliver them to the analytical instruments inside the rover body. This capability is instrumental in the search for traces of past life, as chemical biosignatures are better preserved and more likely to be detectable below the surface [1]. It also enables the investigation of the mineralogy and stratigraphy of the shallow subsurface environment of Mars, providing a more complete understanding of the geology of the landing site, Oxia Planum.
During its operation, the drill system records a broad collection of telemetry data, including temperature, force, torque, and speed readings. Once downlinked to ground, telemetry data enables the assessment of the drilling operation progress and system health status. But drill telemetry can also offer valuable information about the mechanical properties of the rocks the drill bores through, thus providing additional clues about the geology of drilling site. When used in synergy with the information provided by the rover’s science instruments, it can improve the overall characterization of the subsurface environment where core samples are collected and inform their analysis [2].
To this end, we are developing data analysis techniques and custom data processing and visualization tools to extract scientifically relevant information from drill telemetry data.
One of the main goals is to extract information about the stratigraphy of the drilling site. Differences in the mechanical properties of stratigraphy layers are linked to variation in the composition and cohesion state. The detection of such variations can provide information to improve the understanding of the geologic history of the site.
An example of some informative parameters that can be derived from drill telemetry data is shown in Figure 1. Here various quantities are shown against depth, thus highlighting the variability of the mechanical behaviour of different stratigraphy layers. The telemetry dataset shown here comes from a Ground Test Model (GTM) drilling test carried out in February 2023. In this case adjacent stratigraphy layers had very different mechanical properties, making the detection of the interfaces between them rather easy. However, some more advanced techniques will be needed to detect subtler differences. Another example of the variation seen in drill telemetry data corresponding to the interface between two different materials is shown in Figure 2. Here we see the drill moving from a loose material to one that is harder to drill. In addition to the decrease of the vertical speed and increase of drill torque, also the power density spectrum of the torque sensor reading varies. This hints to the information content of the time evolution of the telemetry data. Indeed, most of the best-performing analysis methods we tested so far also use some information about the time evolution of the telemetry data, rather than only using values from a single timestep.
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Figure 1 - Quantities derived from drill telemetry data from February 2023 GTM drilling tests. |
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Figure 2 – Variation of the measured drill torque at the interface between two layers with. |
To assess the information content of the various drilling parameters, we employed several dimensionality reduction and clustering algorithms. These methods are also useful to provide a preliminary assessment of drill telemetry with some “blind” indications about the presence of layers with different properties, without requiring a-priori information. Figure 3 shows a representation of a telemetry dataset in a 2-dimensional embedding space obtained with the t-SNE (t-distributed stochastic neighbour embedding) algorithm. This representation shows similar data points closer together. Here each point represents a 20 second interval of telemetry data and is coloured as a function of depth. However, depth was not included among the features the embedding was computed from, and the fact that lumps of points result to be close together also in depth gives a first indication of the presence of layers with different properties. Similar conclusions can be drawn from the results of clustering algorithms such as HDBSCAN, shown in Figure 4. These results indicate that substantial information about the properties of the material is indeed contained in drill telemetry data.
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Figure 3 - t-SNE visualization of a drill telemetry dataset. |
Figure 4 - HDBSCAN clustering results. |
In addition to the unsupervised learning methods mentioned so far, we also developed some supervised classification models based on 1D convolutional neural networks. After training and hyperparameter tuning, such models achieved a very high accuracy in recognizing different materials, but their general applicability is still limited as they were trained on a limited dataset, with very few reference materials.
We are now working towards generating a larger reference dataset to improve our analysis methods, combining data from both GTM drilling tests and the qualification tests of the drill performed in Mars-like conditions. New GTM drilling tests will be carried out in the future, providing additional data and the opportunity of further enhancements. We are also trying to better define some quantitative metrics to assess and compare the performance of different analysis techniques under different scenarios. In addition, we are working on a more detailed assessment of the information content of drill telemetry data: we aim to investigate the limits of layer interface detection and estimate the accuracy of classification models under more realistic settings. Finally, even more test data will enable the pursuit of a further goal: the development of models that, in addition to a qualitative classification, also provide a direct quantitative estimate of some mechanical properties, such as the uniaxial compressive strength.
References
[1] Vago J.L. et al, Astrobiology, vol 17, n.6-7 (2017)
[2] Altieri F. et al., Advances in Space Research (2023)
How to cite: Rossi, L., Altieri, F., Frigeri, A., De Angelis, S., De Sanctis, M. C., Ferrari, M., Fonte, S., Formisano, M., Pilati, A., Clemente, M. P., Cordeschi, L., Merlo, A., Joudrier, L., Sefton-Nash, E., and Vago, J.: Assessing the information content of rover drill telemetry data for the characterization of the shallow subsurface of Mars, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-638, https://doi.org/10.5194/epsc2024-638, 2024.
Introduction: Oxia Planum (OP) [1] is the selected landing site for the ExoMars Rosalind Franklin (RF) Rover. The goal of the reformulated ExoMars Rosalind Franklin mission, now in planning for launch in 2028, is to search for signs of past and present life and to characterize the water and geochemical environment in the subsurface as a function of depth. RF will accomplish this with its ‘Pasteur’ suite of scientific instruments, and a drilling and sampling subsystem to retrieve samples for analysis from up to 2 m depth [2].
In preparation for the 2022 mission, The ExoMars science team undertook a geological mapping exercise of the landing site [3] prioritizing the 1-sigma area of the 2022 landing ellipses (Fig 1). The goal of this map is to develop a thorough understanding prior to rover operations of the OP landing site’s geography, stratigraphy, and geological history, and to provide testable hypotheses to facilitate interpretation of results and address the mission’s science objectives.
Here we present the completed map of Oxia Planum, our interpretations of the major geological units, the leading hypotheses for some major units and implications for astrobiology goals of the mission.
Figure 1: The compleated map sheet of the 1:25,000 scale landing site map (https://www.tandfonline.com/doi/full/10.1080/17445647.2024.2302361 )
Progress: The compleat map (Figuer 1) is presented at a scale of 1:30,000 and includes 14 bedrock geological units in 6 groups, 6 overlay units and geomorphic linework.
Interpretations and Hypotheses: This map is a detailed investigation into geological units of the proposed landing site; however these units are also representative of the wider Oxia Planum region. To formulate interpretation and hypothesis we incorporate these additional contextual observations and consider a range of possible interpretations and associated confidences presented in [4].
Lower bedrock group (lBg; lBg1, lBg 2, lBg3) –materials with orange tone CaSSIS Near IR Panchromatic Blue channel images strongly associated with phyllosilicate spectral signatures. Also includes brighter ‘knobby’ materials, whether these are stratigraphically distinct layers or lateral variation is unclear. Contextual observation suggests the origin of these units may be the upper part of a lacustrine to alluvial succession [5] but it is also likely that the alteration predominantly occurred in situ [6, 7].
Upper Bedrock group (uBg; uBg1, uBg2, uBg3) – uBg1 forms a thin resistant layer directly underlying Mm and oDm units. uBg2 and uBg3 host a boxwork of upstanding ridges associated with high relief areas such as scarps and large ridges. Regionally extensive, this unit crops out as a mantling layer, and contains exhumed fluvial channel bodies, so an origin related to fluvial and groundwater processes is possible, but this may be reworking of widespread volcanoclastic material.
Mound material (Mm; hMm, rMm) – This unit group constitutes isolated hills (hMm) and ridges (rMm), which are part of a regional population. Mm predates the dark group and appears to be remnants of a ~100 m thick layer [8]. However, deposition and erosion mechanics for the unit are unresolved.
Dark material (Dm; oDm iDm) – Thin (~1 m), rough units with lots of trapped regolith, are found at the top of the stratigraphy (oDm) on local topographic highs in regional topographic lows, or interbedded with the lBg
Bright patches (Bp; cfBp, cBp) – Light toned patches with concentric layers occur in (<100m) relic impact structures or larger (>250m), but not infilled, craters.
Crater materials (Cm; nCM, rCm, dCm) – Material relating to impact craters show degradation states varying from fresh dark ejecta (nCm) to degraded and overlain rims (dCm).
Conclusions: The mapping effort is now completed. Since the resumption of the ExoMars mission we are working towards publication of the map, data and accompanying report to support science activities in preparation for the planned 2028 launch.
Acknowledgments: We thank the CaSSIS and HiRISE teams for ongoing data collection. PF thanks UK Space Agency for funding (ST/W002736/1)
References: [1] Fawdon, et al (2021) Journal of Maps, 17:2, 621-637, [2] Vago, J. et al., (2017) Astrobiology 17 (6–7), 471–510. [3] Sefton-Nash, E. et al., (2021) in LPSC 51, Abs.# 1947. [4] Fawdon P. in LPSC54 abs#2061 [5] Fawdon et al., 2022 JGRp 127, e2021JE007045 [6] Mandon et al, 2022 Astrobiology 2021 21:4, 464-480 [7] McNeil et al, LPSC54 abs#1252 [8] McNeil et al 2022 JGRp 127, e2022JE007246
How to cite: Fawdon, P., Orgel, C., Adeli, S., Balme, M., Calef, F., Davis, J., Frigeri, A., Grindrod, P., Hauber, E., Le Deit, L., Loizeau, D., Nass, A., Quantin-Nataf, C., Sefton-Nash, E., Thomas, N., Torres, I., Vago, J., Volat, M., and De Witte, S. and the ExoMars RSOWG 'macro' Mapping team: The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-850, https://doi.org/10.5194/epsc2024-850, 2024.
Abstract
The WISDOM ground penetrating radar aboard the Rosalind Franklin rover is waiting for its intended launch in 2028 within the ExoMars mission. It will search for Water, Ice, and Subsurface Deposit On Mars (WISDOM) to enhance the knowledge of Oxia Planum on Mars. Meanwhile, the WISDOM team is improving the signal processing, since in general the microwave scattering in the sensing channel is a very complex phenomenon [1]. It is mainly determined by the property of transceiver system (radar), of the wireless channel in the random media and the property of the targets to explore. Regarding the target property, it can be divided into two main factors, namely the geometry/shape and the material properties (frequency-dependent relative permittivity). In practice however, due to the high complexity and sensibility of the random scattering signal tracking and separating of these responses is a challenging task by pre-calibration such that it can deteriorate e.g. the subspace image analysis. With radar systems such as WISDOM, which have a distance of up to several wavelengths between the antenna and the ground, there is furthermore an influence from the environment on the radar coupling, which results in an unknown signal. A reasonable tracking/estimation, especially on-site calibration, of these random signal plays then a major role for the radar technologies in practice and will be outlined in this paper.
1 Introduction
In this paper, we will mainly focus on the random scattering signal analysis for WISDOM and similar GPR-like sensing systems, where the distance between radar system and targets could be very short (close to the antenna near-field). Such that there can be severe signal inter-action between radar and targets.
As a result, both the calibrated radar response and the characteristic response of the target will be distorted and result in unknown signal. In other words, a pre-calibration for radar system and targets in this case will fail. For that, we suggest an on-site coordinate system for those applications.
Regarding concrete applications, it can be summarized (but not limited) as follows:
- on-site calibration
- higher resolution imaging
- geological feature analysis.
For the purpose above, we introduce the kernel function ξ, which describes each independent channel spectral response, for signal modelling.
The whole received signal then consists of a sum of all convolutions between different kernel functions and their channel impulse responses h. Regarding j-th measured data, that is
However, both kernel functions and their channel impulse responses are unknown in general, due to the quasi near-field effect.
2 On-Site Calibration
The on-site calibration for WISDOM is mainly focusing on the free-space response tracking. This free-space is basically the radar initial working circumstance which is influenced by e.g. the rover platform and Mars ground. This means, every new measured data have always its own coordinate system.
The on-site coordinate system will be extracted by the kernel decomposition, particularly of the strong reflected signal, which are usually dominated by the surface reflected signal. The corresponding coordinate system is equivalent as an on-site calibration in terms of free-space circumstance.
Given multiple measurements, by exploring the coherent property among different data, the calibrated kernels and their channel impulse responses can be summarized as
where Δ is the tracking algorithm. This autonomous calibration is important especially for subsurface signal analysis in terms of e.g. subspace imaging and subsurface scattering dictionary construction. Since all subsurface signal can be considered as some kinds of deviation of the surface signal.
3 Higher Resolution Imaging
High spatial resolution for radar imaging is always an important issue which have been discussed and there are different ways for handling this problem. Generally, the radar image resolution (matched filter based) is limited by the system effective signal bandwidth, which is however finite in practice. An approach to extend the bandwidth by extrapolation for improving range resolution is given in [2].
By considering our model in Eq. 1, the mentioned limited spatial resolution is due to the bandwidth-dependent pulse width of kernel function ξi, while its channel impulse response hi is a sequence of Dirac pulses and exhibits unlimited spatial resolution. Therefore, instead of achieving larger bandwidth, we are trying to extract the channel impulse response alternatively. For pursuing hi, a deconvolution of the kernel function ξi is required, which in turn still depends on the on-site response ξi tracking. In other words, kernel tracking (KT) is a dual problem for higher resolution imaging. In practice, both BWE and KT are proposed for cross-validation.
An extended perspective for higher resolution imaging is a higher precise estimation of kernel function ξi, which plays a major role for the geological feature's analysis. Basically, the tracking algorithm in Eq. (2) is an iterative process where ξi and hiare alternatively estimated and tracked. A better estimation of one parameter can improve another parameter estimation. Thus, channel impulse response hi tracking is also a dual problem for kernel function estimation. Finally, higher resolution imaging can be considered as a joint estimation of ξi and hi.
4 Geological Features Analysis
Geological features analysis is basically the core of the WISDOM instrument, where the Mars surface and shallow subsurface properties will be explored. By the WISDOM radar system, these geological features are imprinted mainly over kernel functions ξi, such that kernel function tracking is geological features tracking as well. Certainly, so far we have just indicated this relationship between kernel function and geological properties and therefore cannot describe this relationship explicitly. Besides, this relationship can be distorted easily by all kinds of interference. Nevertheless, one can still present the geological features but in the relative manner, e.g. by unsupervised learning.
References
[1] A. Ishimaru "Wave Propagation and Scattering in Random Media", IEEE Press and Oxford University Press. ISBN 0-7803-3409-4, 1997.
[2] N. Oudart, V. Ciarletti, A. Le Gall, M. Mastrogiuseppe, Y. Hervé, W.-S. Benedix, D. Plettemeier, et al. “Range Resolution Enhancement of WISDOM/ExoMars Radar Soundings by the Bandwidth Extrapolation Technique: Validation and Application to Field Campaign Measurements.” Planetary and Space Science 197 (March 1, 2021): 105173. https://doi.org/10/ght9hk.
How to cite: Benedix, W.-S., Lu, Y., Plettemeier, D., and Ciarletti, V.: On-Site Response Tracking for WISDOM System, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-861, https://doi.org/10.5194/epsc2024-861, 2024.
Introduction: The Rosalind Franklin Rover of the European Space Agency (ESA) will be launched in 2028, as the second part of the ExoMars program. The Rosalind Franklin Rover (RFR) (Fig. 1) will explore the surface and subsurface of Mars in Oxia Planum (18.20°N ; 335.45°E). The aim will be to collect samples of well-preserved organic material down to a depth of 2 m. The Entry-Descent-Landing (EDL) phase of RFR is critical and decisive and requires meeting the engineering threshold constraint for parachute deployment and rover deceleration. Thales Alesia Space Italia is in charge of preparing RFR's EDL. Our contribution to this task is to provide some characterization and forecast of the weather conditions and turbulence in Mars’ atmosphere, for the chosen landing period and area. This is a presentation of the methodology, models and observations/data we will be using.
Figure 1: Representation of Rosalind Franklin Rover on Mars’ surface. (Credits: ESA/Mlabspace)
Methodology: Mars' atmosphere is complex in terms of structure and dynamics. It can be affected by strong winds, presence of water ice clouds and high density of dust particles. The thermal structure of Mars’ atmosphere and its atmospheric circulation are controlled by the amount and transport of airborne dust [1].
Our objective is to represent and characterize Mars’ atmosphere with realistic conditions, while taking into account conditions that can be extreme, to encompass all possible wind and dust density scenarios at the time and in the area of the EDL. To be able to do this fully, models spanning different resolved scales will be used: a General Circulation Model (GCM) that is the Mars PCM (Planetary Climate Model) [2] and the Mars Climate Database (MCD) [2, 3] for global scale, the Mars Mesoscale Model (MMM) [4] for regional scale and microscale model, Large Eddy Simulation (LES) [5], for local turbulence.
Figure 2: Mesoscale domain topography centered on the landing site of Oxia Planum marked by cross.
Numerical Simulations: The landing of RFR is scheduled in 2030, prior to the Martian dusty season (Ls > 180°), after a two-year transfer to Mars. However, although unlikely, the occurrence of local or regional dust storms is plausible and must be taken into account in the simulations. Hence four dust scenarios will be used: climatology, cold (clear atmosphere), warm (dusty atmosphere) and a dedicated scenario (local dust storm). The dedicated scenario will be based on an extrapolation of dust column maps of Mars’ multi-annual climatology of dust distribution (from Mars year 24 to 37) [6, 7] to create a realistic extreme scenario.
Using those dust scenarios, Mars’ atmosphere will be simulated with the Mars PCM and MMM to make regional characterization of the extreme horizontal and vertical winds in Oxia Planum. The mesoscale domain is set to an area ranging from −40° E to −10° E in longitude, and from 0° to 30° N in latitude, covered by 180x180 grid points (Fig. 2) with a horizontal resolution of around 10km. Then, to take into account the convection activity induced by solar surface heating, a local characterization of convective updrafts, downdrafts and shears will be made using LES with an even finer resolution of less than 50m.
Observations and data: The Mars Dust Activity Database (MDAD) [8] and data from instruments such as the spectrometer TES, EMIRS, THEMIS, the radiometer MCS can provide observations of Mars’ atmosphere in Oxia Planum from which water ice cloud horizontal distribution, atmospheric density or temperature profiles can be retrieved.
These observations will serve as a reference to evaluate the outputs of simulations at different scales. And thus makes it possible to assess the possible biases in the simulations that should be taken into account.
References: [1] The Atmosphere and Climate of Mars (2017) ISBN-13: 9781107016187. [2] Forget, F. et al. (1999), J. Geophys. Res., 104, E10, 24155-24176. [3] Millour, E. et al. (2024), 10th Mars Conference. [4] Spiga, A., and F. Forget (2009), J. Geophys. Res., 114, E02009. [5] Spiga, A., et al. (2010) Quarterly Journal of the Royal Meteorological Society, 136:414–428. [6] Montabone, L. et al. (2015) Icarus, 251, pp. 65-95. [7] Montabone, L. et al. (2020) J. Geophys. Res. - Planets. [8] Battalio, M. and Wang, H. (2021), Icarus, 354, 114059.
How to cite: Segonne, C., Millour, E., Montabone, L., Forget, F., and Spiga, A.: Characterization of the Martian atmosphere for ExoMars - Rosalind Franklin Rover Entry-Descent-Landing, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-759, https://doi.org/10.5194/epsc2024-759, 2024.
Introduction
The ESA ExoMars Rover mission will have the task of investigating the Martian soil down to 2 meters providing a physical and chemical characterization of the shallow subsurface by means of an extensible drill [1,2]. For understanding how the drilling activities can affect the already tricky interplay between hydrodynamical and thermal processes that govern the distribution of hypothetical volatile material in the subsurface, numerical models are required. We present preliminary results concerning the evolution of a mixture of ice and water vapour located at a variable depth in the Mars' subsurface through a Smoothed Particle Hydrodynamics (SPH) approach [3]. In addition to show the importance of modelling various physical phenomena like phase transitions and dynamical interactions, we propose a novel approach which consists in coupling the SPH code with Eulerian codes to account for the influence of the drilling activity on the thermal state of the borehole walls.
Methods
Simulations are performed with the help of PySPH [4], an open-source and Python-based framework for SPH. Using a number of pseudo-particles between 20000-30000, we generate a cylindrical fracture with a diameter of about 14 mm and a depth of 12 cm, in which we typically set a layer of ice and water vapour of about 6 cm as shown in Fig.1. The real depth of the hole is computationally unsustainable in the development phase, since it would require a huge number of particles (about 500000) and, consequently, very long simulations. At this point, besides to numerically integrate the hydrodynamics equations that govern the time evolution of the velocity, density, and thermokinetic energy of our multi-component fluid, we need to implement reasonable physical approximations to treat all the other phenomena. Ice-vapour phase transitions are taken into account via a statistical approach by considering the possible sublimation and deposition both for particles in flight and those interacting with Mars' surface. Moreover, dynamical interactions with the internal and external solid boundaries are implemented through a proper mirroring scheme.
In the next steps, we will incorporate into the framework the effects due to the Solar radiation, the viscous drag between solid and gaseous particles, and the heat released on the borehole walls during the drilling operations. For this aim, we assign a temperature gradient to the solid particles of the fracture exploiting the output of an Eulerian code [5].
Figure 1: Typical initial conditions.
Preliminary results
In order to test our code, we applied it to two basics problems: a gas sphere expanding adiabatically in space and a classical three-dimensional shock wave expansion. In the first case our results reproduced satisfactorily the analytical profile of a homologous expansion, while in the second case we found a good agreement both with the analytical solution proposed by Sedov [6] and other Lagrangian codes [7,8]. In Fig.2, the comparison is illustrated between the density profile obtained within our simulation using 100000 pseudo-particles and the analytical counterpart.
Currently, the multi-component fluid is influenced solely by dynamical and thermal interactions with the boundary, as well as by phase transitions, in which we included also the contribution due to the latent heat. In particular, after the inclusion of each effect, we ensured that fundamental conservation laws, such as energy conservation, were fulfilled.
Figure 2: Density profile as a function of the radial distance at a time t = 0.2 s.
Acknowledgments
This work is supported by INAF-IAPS within the project "ExoMars".
Bibliography
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How to cite: Maggioni, L., Teodori, M., Magni, G., Formisano, M., De Sanctis, M. C., and Altieri, F.: Volatile emissions from planetary fractures through a smoothed-particle hydrodynamics approach: the case of Mars, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-312, https://doi.org/10.5194/epsc2024-312, 2024.
Introduction:
CaSSIS is a visible to near-infrared (VNIR) bi-directional push-frame stereo camera onboard the ExoMars 2016 Trace Gas Orbiter (TGO) providing images at ~4.5 m/px (resampled to 4 m/px), < 9.5 km wide and up to ~50 km long with four broadband filters (BLU: 495 PAN: 678 RED: 836 NIR: 939 nm) [1]. This study demonstrates the effectiveness of CaSSIS data as a bridge between HiRISE IRB (~50cm-1m/px) [2] and hyperspectral VNIR+IR CRISM (targeted: ~16-40m/px; mapping ~180 m/px) [3-4] with examples from rover landing sites, active (Jezero, Gale) and future (Oxia Planum).
Methods:
To link and facilitate co-analysis between datasets and maximize the characterization of landing sites, we use a combination of 1) CaSSIS colour modeling, 2) colour transformations (e.g., Decorrelation Stretching - DCS), 3) spectral parameters and 4) a Dark Subtraction (DS) to minimize time-variable atmospheric scatter in the VNIR [5-9].
CaSSIS modeled colours aid with preliminary identification of phases by comparing them with observed CaSSIS NPB, HiRISE IRB, and CaSSIS/HiRISE-equivalent CRISM [7]. Our modeling method calculates the expected colour values for phases based on values from reference spectra for all CaSSIS bands, which are then combined into the four standard R-G-B combinations (i.e., NPB, RPB, NRB and NRP) (Fig. 1). This colour-modeling reveals and highlights the significance of relative colour on Mars. Relative colour is the manifestation of specific colour (rather than the predicted) based on the relative differences between the spectral character of a specific phase and that of the mean background. This may be unique to Fe-poor phases and provides the first explanation for the distinctive pinkish colour of chlorides and some Al-clays (e.g., kaolinite) in colour-infrared images [7, see 10].
We have been investigating the DS correction, recommended by [5] and demonstrated to effectively isolate surface spectral characteristics and facilitate spectral/compositional analysis between the datasets [6-9]. DS is critical for co-analysis as the ratio method employed by CRISM analysts does not work well for HiRISE and CaSSIS [7]. Lastly, DS-corrected CRISM will be compared to rover VISIR SuperCam (2020) and VNIR data from the MastCams (MSL & 2020) and PanCam (ExoMars) to validate phase identification and assess the effectiveness of the DS on orbital datasets.
Results & Discussion:
“Mega”breccia blocks within Jezero Crater.
The geology of the Jezero Crater rim is characterized by the presence of large (10s-100s meters) and spectrally diverse clasts (Figs. 2 and 3); these likely originate from ancient crustal lithologies formed from multiple impact events pre-dating Jezero. Based on their characteristics, the rim also appears to include moderately- to poorly preserved Jezero impact melts; lastly, the rim possesses deposits that are interpreted to be post-Jezero [11-12].
Here we focus on the diverse breccia clasts of the rim. Clasts are comprised of Fe/Mg smectite and LCP [11-13] but may also include HCP- or basaltic blocks and kaolinite. Kaolinite is characteristically pinkish in colour [7], which is identified at a few locations (Fig. 2). Fig. 3 shows linkages clasts of the western rim, while Fig. 4 focuses on the southwestern rim. LCP is a greenish cyan (Fig. 4a; c.f., Fig. 1), which is accentuated in DCS image (Fig. 4b) and corresponds to bluish colours in a CBRC image (Fig. 4c); both DCS and CBRC are more useful than a standard R-G-B due to the minimization of illumination effects. A CaSSIS PAN-NIR Ratio (PNR) effectively highlights LCP supported by how well it matches with the CRISM LCPINDEX (c.f., Fig. 4d & 4e). This is likely due to the ~900-1000 nm absorption for LCP falling well within the sensitivity range of CaSSIS. Lastly, DS-corrected spectra spanning all 3 datasets (Fig. 4f) show remarkable consistency, demonstrating the effectiveness of the correction to facilitate the co-analysis of these datasets.
CaSSIS characterization of hematite at Gale.
Hematite has a unique magenta colour in CaSSIS NRP images and a 4-point spectrum that makes it arguably identifiable with CaSSIS alone; the key is the “RED” IR-band (~836 nm) along with the PAN and NIR bands on either side, which just resolves the absorption around 850 nm (Fig. 5) [14]. Unfortunately, HiRISE does not possess this added spectral sensitivity. In addition to Gale [15-17] (Fig. 6), we have identified hematite at Meridiani Planum, Capri Chasma, and Aram Chaos with CaSSIS.
Clays and LCP in Oxia Planum.
Compared to other landing sites, Oxia Planum lacks coverage of targeted CRISM cubes. CaSSIS is particularly well-suited to extend this paucity of information needed for landing site characterization and mapping [18]. Fe/Mg semctites have a characteristic orange colour and are distinct from the more yellowish ferric dust (Fig. 6). CaSSIS provides more coverage, including by the limited colour swath of HiRISE, and is well suited to mapping out both the orange and blue subunits of the clay. We also recently discovered LCP in Oxia [19] (Fig. 6), which we continue to explore with new data from CaSSIS and HiRISE. We are nearing completion on the first CaSSIS quantitative mosaic of the site to augment existing maps [e.g., 18] and be used as an effective tool for long-term planning and context.
References: [1] Thomas et al. (2017) Space Sci. Rev., 212, 1897. [2] McEwen et al. (2007) JGR Planet., 112 [3] Murchie et al. (2007) JGR Planet., 112. [4] Seelos, F. (2022) LPSC, 2361. [5] Tornabene et al. (2018) Space Sci. Rev., 214. [6] Tornabene et al. (2022), LPSC, 2330. [7] Tornabene et al. (2024) Space Sci. Rev., in prep. [8] Rangarajan et al. (2023a) Icarus, 115443. [9] Rangarajan et al. (2023b) Icarus, 115849. [10] Rangarajan et al. (2024) EPSC, this conference. [11] Mayhew et al. (2024) LPSC. [12] Scheller et al. (2024) LPSC. [13] Scheller and Ehlmann (2020) JGR Planet., 125. [14] Morris et al. (1985) JGR, 90. [15] Milliken et al. (2010) GRL, 37. [16] Fraeman et al. (2013) Geology, 41. [17] Fraeman et al. (2020) JGR-Planet., 125. [18] Fawdon et al. (2024) J. Maps., 20. [19] Tornabene et al. (2023) LPSC.
How to cite: Tornabene, L. L., Rangarajan, V., Osinski, G., Cremonese, G., Fawdon, P., Grindrod, P., Nobelt, A., Pajola, M., Piatek, J., Stabbins, R., and Thomas, N.: Utility of ExoMars-TGO/CaSSIS to facilitate co-analysis of CRISM and HiRISE for detailed characterization of the surface: Examples from active and future rover landing sites, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1321, https://doi.org/10.5194/epsc2024-1321, 2024.