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Record W3163547712 · doi:10.1061/9780784483374.093

Dusty Thermal Vacuum (DTVAC) Facility Payloads Operations under Simulated Lunar Environment

2021· article· en· W3163547712 on OpenAlexaff
Roman V. Kruzelecky, Piotr Murzionak, Paul Burbulea, Martin Mena, Ian Sinclair, Gregory W. Schinn, E. A. Cloutis

Bibliographic record

VenueEarth and Space 2021 · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of WinnipegMPB Technologies & Communications (Canada)
Fundersnot available
KeywordsOutgassingCryocoolerShroudRegolithThermocoupleResidual gas analyzerNuclear engineeringMars Exploration ProgramEnvironmental scienceMaterials scienceAerospace engineeringMechanical engineeringEngineeringPhysicsAstrobiologyComposite material

Abstract

fetched live from OpenAlex

The dusty thermal vacuum (DTVAC) lunar and/or Mars environmental testing facility was designed and built to simulate the relatively extreme lunar near-surface conditions. DTVAC can accommodate test devices up to 1 × 1 × 0.9 m3 in volume, including smaller robotic assemblies, small drill assemblies, science payloads, and surface devices such as radiators and solar panels. Depending on the testing requirements, cooling can be provided either using a recirculating chiller to about 213 K or using LN2 down to about 90 K. In addition, cooling within the DTVAC facility to 41 K using liquid helium was successfully validated on a smaller, 0.25 m × 0.25 m, platen covered with lunar regolith simulant. For the LHe platen cooling, the shroud was cooled using LN2 to provide a thermal buffer. Recently, the DTVAC facility was equipped with an additional 25 Type-T thermocouples to improve its temperature monitoring capabilities, and a 1 to 200 amu residual gas analyzer (RGA) in order to identify the molecular composition of any outgassing from articles under test. A LN2-cooled cold finger was also installed to assist the system vacuum pump down and to facilitate the study of in-situ volatiles. This paper reviews the DTVAC upgrades, functionality calibrations, and summarizes its current capabilities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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 teacher head, not a consensus.

Study designObservational
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

Citations4
Published2021
Admission routes1
Has abstractyes

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