Experimental Simulation of Intimate Water Ice and Regolith Mixtures at Lyman-Alpha Wavelengths for Lunar Permanently Shadowed Region (PSR) Prospecting
Notice bibliographique
Résumé
Background: The Permanently Shadowed Regions (PSRs) of the Moon are thought to contain water ice [1], which is a vital resource for on-site production of breathable air, potable water and rocket fuel. While the study of PSRs on the Moon is a benefit to both space exploration and scientific knowledge, observing water ice in PSRs is difficult due to the low levels of scattered sunlight or earthshine in these locations. However, scattered sunlight from crater walls and starlight in the form of Lyman-alpha photons (121 nm) both provide a faint light source in the VUV spectrum that has previously been used for passive reflectance spectroscopy in PSRs [2, 3].Godin et al. [4] explored the feasibility of using Lyman-alpha wavelengths to detect water ice on the lunar surface. A key limitation of this study was the inability of the experimental setup to simulate intimate regolith-ice mixtures due to sublimation of water ice over time, resulting in the formation of a dust lag layer at the surface of samples no matter how little dust they contained.This lag presents significant limitations to our understanding of this technology’s application in lunar environments, since water ice is likely to exist as small ice grains mixed with regolith on the surface of PSRs, rather than as surface water frost [5, 6, 7]. This study bridges the current knowledge gap by tackling the issue of rapidly sublimating water ice in laboratory-simulated ice-regolith mixtures. Building upon the work done by Godin et al., we have developed a passive thermal shroud to limit the sublimation of water ice in intimate ice-regolith mixtures.Methodology: The shroud (fig. 1) is manufactured from copper due to the material’s high thermally conductivity and capacitance. The thermal shroud sits atop a cold plate, such that it is in contact with the liquid nitrogen exchanger. This will act as a barrier to the radiative heating from the chamber walls, thereby cooling the enclosed environment containing samples of water ice-regolith mixtures to prevent ice from sublimating in the time it takes for the lunar simulator to stabilize.The passive thermal shroud consists of several parts which fit together for easy and quick assembly inside the simulation chamber. The shroud also includes cutouts which will allow for the lamp and camera components to see the sample tray.This study follows the well-established methodology employed by Godin’s experiment, using a Vacuum Ultraviolet (VUV) Camera supplied by our industry partner, Resonance Ltd., to image intimate mixtures of lunar regolith simulant and ice in linearly increasing concentrations (i.e. starting from 10% ice, 90% regolith by weight). We expect to see linear variation in brightness detected by the VUV camera as water ice concentrations in ice-regolith samples are increased.Preliminary experiments indicate that with sufficient pre-cooling of all components (i.e. experimental chamber, sample tray and shroud tiles) water ice-regolith slurries remain intact, with no visible evidence of sublimation. Pictured in Figure 1 is a slurry with 10% by weight regolith and 90% by weight water ice after reaching 6×10-4 Torr in the cryovacuum chamber and being brought back to atmospheric conditions. Ice crystals are present throughout the sample, not just at a top layer, indicating that the water ice observed is not surface frost.Figure 1: Visual image of 10% regolith and 90% water ice slurry after cycle through cryovacuum chamber and brought back to atmospheric conditions. The sample sits atop a cold plate, within the assembled copper tiles forming the thermal shroud.We succesfully captured Lyman-alpha images of the sample pictured in Figure 1 with no evidence of a dust lag layer (fig.2). The same camera settings identified by Godin et al. were used to capture the UV images, with a gain of 29dB and exposure time of 3800ms. The sample is circled in red for visibility. Further investigations comparing Lyman-alpha images of water ice-regolith slurries against pure water ice and pure regolith samples will be done to ascertain a linear increase in brightness with increasing concentrations of regolith.Figure 2: Lyman-alpha UV image of 10% regolith and 90% water ice slurry, taken at 29dB gain and 3800ms exposure time.Once the detection capability of Lyman-alpha technology is verified for intimate mixtures of lunar regolith and water ice, this project can be expanded to investigate other factors which may affect imaging with a Lyman-alpha camera. The camera system may then be used to observe more complex ice mixtures known to exist on the lunar surface (i.e. containing water ice mixed with CH4, SO2, H2S and CO2), commonly referred to as “hypervolatiles” [8].Impact: This study will validate the use of Lyman-alpha cameras for in-situ detection of water ice in permanently shadowed regions of the Moon. Such technology will further the scientific community’s understanding lunar water ice properties and pave the way for further development and optimization of ISRU techniques and prospecting of water ice in the lunar PSRs.References: [1] Colaprete, A., et al. (2010) Science, 330(6003), 463–468. [2] Gladstone, G. R., et al. (2009) Space Science Reviews, 150(1-4), 161–181. [3] Kloos, J. L., Moores, J. E., Godin, P. J., & Cloutis, E. (2021) Acta Astronautica, 178, 432–451. [4] Godin, P. J., Kloos, J. L., Seguin, A., & Moores, J. E. (2020) Acta Astronautica, 177, 604–610. [5] Gladstone, G. R., et al. (2012) JGR, 117, E00H04. [6] Colaprete, A., et al. (2016) [White paper] NASA. [7] Hayne, Paul O., et al. (2015) Icarus, 255, 58-69. [8] Hayes, C. W., Minton, D. A., Kloos, J. L., & Moores, J. E. (2024) Journal of Geophysical Research Planets, 129(7).
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».