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Record W4321492726 · doi:10.5194/egusphere-egu23-1163

Effects of the Lunar Regolith Structure and of the Solar Wind Properties on the Backscattered Energetic Neutral Atoms Flux

2023· preprint· en· W4321492726 on OpenAlexaff
Sébastien Verkercke, Jean‐Yves Chaufray, François Leblanc, Eduardo M. Bringa, Diego Tramontina, Liam S. Morrissey, A. K. Woodson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRegolithSolar windAstrobiologyFlux (metallurgy)PhysicsChemical physicsComputational physicsMaterials sciencePlasma

Abstract

fetched live from OpenAlex

Airless planetary bodies’ surfaces, such as the Moon’s or Mercury’s, are composed of porous regoliths which interact directly with the impinging solar wind. In the case of the Moon, this incoming flux of solar protons has been observed to be partially neutralized and backscattered as Energetic Neutral Atoms (ENA) with reflection coefficients believed to be ranging between ⁓0.1 and 0.2 depending on the study and/or the measurement. Such a large range of reflection coefficients reflects the diversity in the regolith’s interactions with the solar wind and underlines the lack of understanding of the lunar regolith and its influence on the particles impacting it.The ENA flux is thought to depend on the structure of the upper regolith layer and the solar wind characteristics. By using a model combining a Monte Carlo approach to describe a solar proton’s journey through the lunar surface, with molecular dynamics to characterize its interactions with the regolith’s grains, we highlighted key parameters which influence the backscattered ENA flux and analyzed their roles in these interactions. To describe the structure of the lunar regolith we used the open-source code LAMMPS Molecular Dynamics Simulator, which allows a realistic description of grain-on-grain contacts using a Johnson-Kendall-Roberts (JKR) contact model. The porosity of the modeled regolith is shown to be dictated by the surface energy of the grains. By considering silicate grains and a realistic range of surface energy for this material, we studied regoliths’ porosities ranging from ~0.5 to 0.85. This work showed that a large porosity favors deeper penetration of the protons inside the regolith, which increases the number of collisions, and thus the energy lost by the impinging protons and their absorption. By accounting for particular directions of observation with respect to the solar wind direction, we showed that the angular distribution of the backscattered ENA is anisotropic. We here used IBEX observations and its characteristic 90° observation angle as a demonstration of the influence of this anisotropy. We finally analyzed the effects of both the energy distribution of the hydrogen atoms after a collision with a grain and the solar wind properties on the ENA energy flux spectrum shape. The modelled spectrum was also compared to the observations of Chandrayaan-1. This work aims for a better understanding of the interactions ongoing at this interface and intents to look into the possibility to deduce information on the surface structure solely from ENA flux measurements.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.191
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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