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Record W2621884505 · doi:10.4050/f-0071-2015-10288

Pilot Head and Body Vibration in Response to Main Rotor Track-and-Balance Tuning

2015· article· en· W2621884505 on OpenAlexaff
Gordon A. Craig, Heather E. Wright, Marc Alexander, Jocelyn Keillor

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsVibrationTrack (disk drive)Head (geology)Balance (ability)Rotor (electric)Computer scienceControl theory (sociology)AcousticsEngineeringPhysical medicine and rehabilitationPhysicsMechanical engineeringGeologyMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

While night vision goggles (NVG) have become an essential part of rotorcraft night flight operations for the military, there has been an increase in the reports of neck strain and neck pain in flight crews using the equipment. The neck is required to support the weight of the NVG on the helmet and is constantly stabilizing the head to counteract the helicopter vibrations. The current flight tests examined the magnitude of vibrations at the pilot's head while tuning or slightly de-tuning the track-and-balance of the main rotor on the NRC Bell 412 as well as measuring the physiological response of the pilot to the resulting vibration levels. While the minimal detuning of the main rotor increased the vibration of the helicopter (by about 0.006g), the increase in vibration at the pilots head was substantial (a 0.01g increase). Physiological measures showed increased heart rate and decreased tactile sensitivity as the helicopter vibration increased. While it is likely that the increased vibration resulting from poor rotor track-and-balance increases the level of neck strain on pilots, further research is required to determine the magnitude of these effects and the maximum safe exposure level.

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 score0.954
Threshold uncertainty score0.290

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 head0.022
GPT teacher head0.254
Teacher spread0.232 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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