MétaCan
Menu
Back to cohort
Record W1997125399 · doi:10.5589/q09-014

Spacecraft damage assessment due to hypervelocity impacts using a micrometeoroid and orbital debris detection system

2009· article· en· W1997125399 on OpenAlexvenueno aff
R. C. Tennyson

Bibliographic record

VenueCanadian aeronautics and space journal · 2009
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsnot available
Fundersnot available
KeywordsHypervelocityMicrometeoroidSpacecraftSpace debrisAerospace engineeringSpace suitKevlarAstrobiologyMaterials scienceEngineeringPhysicsAstronomyComposite material

Abstract

fetched live from OpenAlex

This paper describes the design, construction, and testing of a hypervelocity impact (HVI) detection system for monitoring the occurrence of an impact, the location of the impact, and the resulting damage to a spacecraft. One of the constant dangers emanating from the space environment is the presence of micrometeoroids and space debris. The energy associated with these hypervelocity impacts is sufficient to penetrate most spacecraft structures, damage spacecraft components, and pose a potential threat to human occupants. A detection system has been developed involving optical fibers woven in an orthogonal grid in a fabric such as Kevlar. The optical fibers are interrogated by a light source that monitors the intensity of the light transmission. Changes in light transmission relate to HVI damage to the optical fibers such that a damage zone can be constructed based on these data. This “smart fabric” can be bonded to critical parts of the spacecraft susceptible to HVI damage or mounted inside the spacecraft structure such that the HVI particles are attenuated before they can damage interior components (and astronauts). Tests on a Kevlar smart fabric have been conducted at the National Aeronautics and Space Administration (NASA) Johnson Space Center using aluminum plate targets, and results are presented demonstrating the effectiveness of this technique.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score1.000

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCanadian aeronautics and space journalSame topicSpace Satellite Systems and ControlFrench-language works237,207