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Record W4283215766 · doi:10.2514/6.2022-3894

Determining Rotor-Hub Loads of Tandem Rotor Aircraft

2022· article· en· W4283215766 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

VenueAIAA AVIATION 2022 Forum · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRotor (electric)Blade (archaeology)Helicopter rotorBlade element theoryEquations of motionStructural engineeringTandemAerospace engineeringEngineeringControl theory (sociology)Computer scienceMechanical engineeringPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2022-3894.vid As part of an aircraft fatigue assessment program, the rotor loads of a tandem-rotor helicopter are deduced via flight test measurements. During in-flight maneuvers, accelerations and angular displacements of the rotor blades were measured. After correcting the measurements for installation errors, the experimental data and the blade mass properties were used in the rotor blade equations of motion, in order to derive the hub loads. Aside from describing the experimental setup and data reduction, the development of the equations of motion of a fully articulated rotor blade and a solution approach is outlined in this paper. The resulting hub loads deduced from the blade equations of motion are compared to several sources.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score0.670

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 head0.011
GPT teacher head0.255
Teacher spread0.244 · 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