MétaCan
Menu
Back to cohort
Record W2057020885 · doi:10.2514/2.4566

Minimization of Vibration of Spacecraft Appendages During Shape Control Using Smart Structures

2000· article· en· W2057020885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Guidance Control and Dynamics · 2000
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsSpacecraftAppendageControl theory (sociology)VibrationComputer scienceAerospace engineeringMinificationTrajectoryVibration controlControl (management)EngineeringControl engineeringGeologyAcousticsPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

the range ( i 23.0 deg, 23.0 deg) or j h 2 j > 35 deg to avoid an S1-S2 close-contact possibility. Note again that arriving at these conclusions throughMC analysis is computationallydemanding and time consuming because many combinations have to be tried in which a large number of simulations (orbit propagation) for each of the combinations is carried out. Althoughthe strategyis demonstratedin the case of two satellites, it can be used even when there are more satellites to Ž nd deployment conditionsfor each satellite to avoida close-contactpossibility among all of them. A system of separation springs for satellites can be designed to meet the noncollisionseparationvelocity taking into account themasses.Also, orientationcan be plannedthroughproper control strategies. The orientation angle leading to recontact of P and S1 and P and S2 can also be computed using this strategy. For this example, no angle leads to such a recontactpossibilitybetween P and S1 and an angle of approximately90 deg leads to the collision of P and S2.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.498

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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