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Record W2623992961 · doi:10.4050/f-0071-2015-10161

Experimental Validation of Tailboom Vibration Control Using Fluidic Flexible Matrix Composite Tubes

2015· article· en· W2623992961 on OpenAlexaff
Kentaro Miura, Peter Romano, Matthew J. Krott, Edward Smith, Christopher D. Rahn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsBell Helicopter Textron (Canada)
Fundersnot available
KeywordsComposite numberFluidicsVibrationMaterials scienceMatrix (chemical analysis)Composite materialStructural engineeringMechanical engineeringComputer scienceAcousticsEngineeringPhysicsAerospace engineering

Abstract

fetched live from OpenAlex

Rotorcraft tailbooms experience driveline component wear and structural fatigue, while causing passenger discomfort due to vibration excitation from the rotors, separated flow behind the rotor hub, vehicle maneuvers, and wind gusts. Fluidic Flexible Matrix Composite (F²MC) tubes, a new class of passive fluidic vibration treatments, are tested on a representative tailboom structure. Two pairs of F²MC tubes are mounted to the top and bottom of the tailboom and interconnected via a fluidic circuit with a tunable orifice to form a tuned vibration absorber. Experimental frequency responses are obtained to demonstrate that the tuned vibration absorber reduces response amplitude at the first vertical bending mode by over 70%, and that a partially closed orifice leads to a damped absorber that adds nearly 8% damping to the first mode. A model of a tailboom with F²MC tubes is developed and validated with the experimental results. The effect of fluid pre-pressure and tailboom forcing amplitude are studied.

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 score0.402
Threshold uncertainty score0.377

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 head0.028
GPT teacher head0.265
Teacher spread0.237 · 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
Published2015
Admission routes1
Has abstractyes

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