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Record W4401804143 · doi:10.4050/f-0080-2024-1041

Development and Flight Demonstration of An Active Seat Mount System for Aircrew Whole-Body Vibration Mitigation on NRC Bell-412 Helicopter

2024· article· en· W4401804143 on OpenAlexaff
Yong Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAircrewAeronauticsMountVibrationAerospace engineeringEngineeringAutomotive engineeringComputer scienceMechanical engineeringPhysicsAcoustics

Abstract

fetched live from OpenAlex

Helicopter aircrew are exposed to high levels of whole-body vibration (WBV) in fight operations, which may degrade their ride comfort and performance in the short-term, and contribute to some health issues in the long-term. This paper presents the latest development and flight test demonstration results of an active seat mount system that is designed to reduce helicopter aircrew WBV levels through active cancellation of the N/rev vibration peaks related to the helicopter main rotor speed. A prototype airworthy hardware of the active seat mount system has been developed based on previous bench-top-test designs to meet airframe integrity requirements for installation and flight testing on the Bell-412 helicopter. Extensive experimental results on human occupants using a shaker table facility and flight demonstrations on the NRC Bell-412 helicopter in representative flight conditions are presented and discussed. The active seat mount system has achieved significant reduction to the occupant WBV levels at the bottom seat cushion interface per ISO2631/MIL-STD-1472G metrics, and also showed effective mitigation to the occupant head vibrations. These investigations demonstrate that the active seat mount technology is a feasible solution for helicopter aircrew WBV mitigation.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.533

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 head0.016
GPT teacher head0.310
Teacher spread0.294 · 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
Published2024
Admission routes1
Has abstractyes

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