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Record W1597785131

Experimental study of propeller-aircraft run-up noise

2001· article· en· W1597785131 on OpenAlexaffvenue
Pierre Germain, Jignan Guo, Murray Hodgson

Bibliographic record

VenueCanadian acoustics · 2001
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNoise (video)AcousticsDirectivityAircraft noisePropellerInsertion lossFence (mathematics)Environmental scienceEngineeringPhysicsTelecommunicationsElectrical engineeringMarine engineeringComputer scienceNoise reductionStructural engineeringAntenna (radio)
DOInot available

Abstract

fetched live from OpenAlex

Measurements were made of the characteristics of the noise radiated by a Beechcraft 1900D twin-propeller aircraft during engine run-up. The objective was to determine the feasibility of controlling this noise using active noise control. Total noise levels varied with aircraft heading from 103 to 112 dB (100 to 109 dBA) at 73 m from the aircraft. Noise directivity plots were generated. Levels at the nearest community 3 km away varied from 74 to 77 dB (62 to 66 dBA). Near the aircraft the noise spectra comprised a series of equally-high peaks at the 112-Hz fundamental frequency and its multiples. In the community, the three lowest peaks dominated the A-weighted spectrum, with higher-frequency peaks being progressively attenuated. A coherence analysis was performed on the noises measured at 73 m and 98 m from the aircraft. The insertion loss of a blast fence near the run-up area was estimated from run-up noise measurements made on both sides of the fence. The insertion loss varied from 4 to 13 dB and was greatest at mid frequencies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2001
Admission routes2
Has abstractyes

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