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Record W2334576287 · doi:10.1061/9780784412190.017

Inspection Technique for Reliability Analysis of Lunar Rover Wheel Designs

2012· article· en· W2334576287 on OpenAlexaffabout
Karim Kamal Parbatani, V. Thomson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoil Mechanics and Vehicle Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsPayload (computing)Reliability (semiconductor)TorqueComputer scienceReaction wheelRegolithSpacecraftAutomotive engineeringMechanical engineeringReliability engineeringEngineeringAerospace engineeringAstrobiology

Abstract

fetched live from OpenAlex

A technique is presented that evaluates the reliability of lunar rover wheel designs where data for operation in the lunar environment are not available for traditional reliability analysis. The visual inspection technique is described and an analysis of five historical wheels and four new wheels designed by McGill University is given. The wheel designs were visually analysed according to specific criteria with regard to potential failure under lunar conditions (temperature, vacuum, regolith) considering wear resistance, thermal compatibility, excess loading, torque, etc. Potential wheel performance was quantified using a numerical scale with regard to potential failure due to events, such as temperature fluctuation, wheel-rock impact, excess payload, abrasive wear, etc. The best designs were the Apollo 17 wire mesh wheel (historical) and the iRing wheel (McGill). A reliability checklist which can serve as a guideline to avoid unreliable design features is given.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.755
Threshold uncertainty score0.250

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)0.0000.000

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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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.

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

Citations1
Published2012
Admission routes2
Has abstractyes

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