Resource Reconnaissance for Future Crewed Missions to Mars 
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Notice bibliographique
Résumé
Mars offers abundant raw materials that are of potential value for future human endeavors. Numerous vital elements can be found directly at the surface. The exploration of these natural resource deposits, the concentration of the raw materials contained in them, and the feasibility of mining and refinement are open questions that require further consideration. The natural geological variations in ore deposits can significantly impact viability of exploration sites and of the engineering architecture. Therefore, comprehension of these features is crucial for selecting and optimizing a particular technical design. This underlines the need for accurate resource exploration missions. Refinement and restructuring must be investigated to provide reliable fabrication systems since In Situ Resource Utilization (ISRU) is able to drastically cut down logistical dependence from Earth.Water is an essential requirement for an extended stay on Mars. It will serve as a consumable for astronauts and is needed for the production of propellant and oxygen, and for construction use. Water could even serve as radiation shielding if procurable in sufficient amounts. In contrast to subterranean ice, hydrated minerals offer a promising and reliable potential for water extraction directly at the surface of Mars and at lower latitudes. A large diversity of hydrated minerals such as phyllosilicates, hydrated silica, zeolites, and sulfates have been detected from orbit using visible near infrared (VIS-NIR) reflectance spectroscopy [1-3]. We address the concept of harvesting resources in situ by reviewing the potential of several large deposits of hydrated minerals found on the surface of Mars thanks to previous orbital detections (Fig. 1). We also present estimates of water volumes potentially retrievable from specific deposits and describe additional uses of the hydrated minerals for example as feedstock for a Bio-regenerative Life-Support System (BLSS).A BLSS architecture tends to be superior in terms of mass efficiency compared to non-bio-regenerative, i.e., chemical or physical life support systems, especially for protracted mission durations [4]. BLSS have the unique advantage of managing biological waste through biological processes exclusively. In addition, if higher plants are cultivated, they offer psychological comforts and nutritional benefits derived from the presence of plant life and as fresh food [5]. Thus, BLSS systems realized in the form of one or multiple greenhouses, are an indispensable component for sustaining a human presence on Martian terrain [6, 7]. Over the last 40 years, several studies have shown that crops can be efficiently grown on hydroponic or soilless media [8, 9]. In fact, crop cultivation in controlled environments can even meet or surpass record yields [10]. From 2018 to 2022, the EDEN ISS project from the German Aerospace Center operated a space-analog test facility greenhouse near the Neumayer III station in Antarctica, potentially resulting in the closest Mars analog we can find on Earth (Fig. 2). In the first year of operation, 268 kg of edible biomass was produced on the 12.5 m2 cultivation area of the greenhouse [11] with soilless media. Additional advantages include removing CO2 from the atmosphere, keeping water in a recycling loop, and producing oxygen. These findings demonstrate the importance of BLSS and can provide a scalable estimate of the potential contribution to logistics and required transport of materials for long duration crewed missions. [1]      S.L. Murchie et al. (2009). A synthesis of Martian aqueous mineralogy after 1 Mars year of observations from the Mars Reconnaissance Orbiter, J Geophys Res Planets 114. https://doi.org/10.1029/2009JE003342. [2]      J.F. Mustard et al. (2008). Hydrated silicate minerals on Mars observed by the Mars Reconnaissance Orbiter CRISM instrument, Nature 454, 305–309. https://doi.org/10.1038/nature07097. [3]      B.L. Ehlmann, C.S. Edwards (2014). Mineralogy of the Martian Surface, Annu Rev Earth Planet Sci 42, 291–315. https://doi.org/10.1146/annurev-earth-060313-055024. [4]      C. Lasseur (2010). Melissa: The European project of a closed life support system, Gravitational and Space Biology 23 (2). [5]      C. Mitchell (1994). Bioregenerative life-support systems, Am J Clin Nutr, 60 820S-824S. https://doi.org/10.1093/ajcn/60.5.820S. [6]      M. Bamsey et al. (2009). Canadian advanced life support capacities and future directions, Advances in Space Research 44, 151–161. https://doi.org/10.1016/j.asr.2009.03.024. [7]      H. Liu et al. (2021). Review of research into bioregenerative life support system(s) which can support humans living in space, Life Sci Space Res (Amst) 31, 113–120. https://doi.org/10.1016/j.lssr.2021.09.003. [8]      J.F. Thomas, C.D. Raper (1983) Photoperiod Effects on Soybean Growth during the Onset of Reproductive Development under Various Temperature Regimes, Botanical Gazette 144, 471–476. http://www.jstor.org/stable/2474450. [9]      Y. Tako (2001). Integration of Sequential Cultivation of Main Crops and Gas and Water Processing Subsystems Using Closed Ecology Experiment Facilities, https://doi.org/10.4271/2001-01-2133. [10]    R.M. Wheeler, T.W. Tibbitts (1987). Utilization of potatoes for life support systems in space: III. Productivity at successive harvest dates under 12-H and 24-H photoperiods, Am Potato J 64, 311–320. https://doi.org/10.1007/BF02853523. [11]    P. Zabel et al. (2020). Biomass Production of the EDEN ISS Space Greenhouse in Antarctica During the 2018 Experiment Phase, Front Plant Sci 11. https://doi.org/10.3389/fpls.2020.00656.  Figure 1: Color-coded Mars Orbiter Laser Altimeter (MOLA) map showing the example regions in dashed white box. Figure 2: The EDEN ISS greenhouse in Antarctica with the Neumayer III station in the background (top). Cultivation area inside the test container (bottom).  
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle