MétaCan
Menu
← Back to cohort
Record W7045131607

Assessment of Geo-mechanical properties of lunar simulants

2022· article· en· W7045131607 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsRegolithLunar soilHabitabilityLunar mareExploration of MarsSpace explorationMartian
DOInot available

Abstract

fetched live from OpenAlex

Abstract\nSophisticated manned and unmanned lunar missions are being developed by international collaborations of the USA, Canada, EU, India, China, Japan etc. for a long-term human presence on the moon. These lunar missions require prototype testing of rovers and other hardware on the earth to successfully interact with the lunar surface. This laboratory testing requires various simulant (terrestrial soil mimicking one or more lunar regolith characteristics) testbeds. Actual lunar soil is too pristine and scarce to be used for destructive testing. Hence, simulants have been developed by research institutions, space research organizations, or commercial manufacturers to cater to a wide range of applications. The geotechnical engineering applications of simulants are of paramount importance for the testing of in-situ hardware prototypes and lunar rovers. Although there has been significant development of different forms of simulants, in general, the lunar simulants developed in the last few years are under characterized or uncharacterized from a geotechnical engineering perspective. This research study aims to reduce the gap with the effective geotechnical characterization of seven lunar simulants interpreted with up-to-date soil mechanics theory. Additionally, benchmark terrestrial soils and a Martian simulant (MMS-1) were also tested and a comparison between the lunar simulants and these soils was done to evaluate the possible use of abundantly available soils, as a potential feedstock or raw material to develop lunar simulants.\nThe selected lunar simulants include a mix of lunar mare and lunar highland simulants (CAS-1, EAC-1, OPRL2N, LMS-1, LHS-1, OPRH2N, OB-1A) and they were tested for basic geotechnical properties, stress-strain relationships, and dynamic properties. Resonant column testing of lunar simulants is not known to have been performed before. The experimental regime consisted of tests at relatively low pressures, different relative densities, and with 100% dry conditions. The lunar simulants are finer compared to terrestrial soils. Several properties (PSD, shear strength, Cc) of tested lunar simulants fall within the range of the values of lunar regolith. The mineralogy, particle size distribution, and particle shapes of the materials were found to have a considerable influence on the geotechnical properties of the lunar simulants. The general trends of stress-strain relationships and dynamic properties follow those of terrestrial soils. However, the unique mineralogical components of basalt, anorthosites, plagioclase feldspar etc. in the lunar simulants compared to terrestrial soils tend to give higher values of several parameters (peak friction angle, shear wave velocity, etc.) compared to terrestrial soils. The results when viewed alongside the data of terrestrial soils suggest that a judicious choice of benchmark terrestrial soils might allow the development of lunar simulants with an enhanced fidelity to lunar regolith. In addition, the crushed nature of many of these lunar simulants needs to be investigated in further detail given how significantly the geotechnical properties seem to be influenced by this aspect of the simulants.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.100
GPT teacher head0.300
Teacher spread0.201 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueScholarship@Western (Western University)→Same topicPlanetary Science and Exploration→French-language works237,207→