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Record W2020600019 · doi:10.2514/1.27914

Smart Spring Control of Vibration on Helicopter Rotor Blades

2009· article· en· W2020600019 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Aircraft · 2009
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsCarleton University
FundersNational Research Council CanadaNational Technical University of Athens
KeywordsSpring (device)Structural engineeringDisplacement (psychology)StiffnessCoil springVibrationSmart materialActuatorControl theory (sociology)Moment of inertiaEngineeringMaterials sciencePhysicsAcousticsComputer scienceElectrical engineeringComposite materialClassical mechanics

Abstract

fetched live from OpenAlex

c1, c2 = Smart Spring viscous damping coefficients associated with primary and secondary load paths F = external (input) force applied to the Smart Spring k = effective dynamic stiffness of the Smart Spring k1, k2 = Smart Spring constants associated with primary and secondary load paths m = effective inertia of the Smart Spring m1, m2 = mass of external and internal sleeves in the Smart Spring N = contact force applied by piezoelectric stack T = Smart Spring period of actuation t = time x = displacement (output) yielded by the Smart Spring y = displacement associated with the Smart Spring secondary load path = dynamic stiffness complex coefficients = dry friction coefficient = Smart Spring control frequency, 2 =T ! = Smart Spring frequency of excitation

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.322

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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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