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Record W1997393951 · doi:10.1121/1.1628248

Active local control of propeller-aircraft run-up noise

2003· article· en· W1997393951 on OpenAlexafffundabout
Murray Hodgson, Jingnan Guo, Pierre Germain

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2003
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPropellerNoise (video)AcousticsAircraft noiseNoise controlActive noise controlEnvironmental scienceControl (management)Computer scienceAeronauticsMarine engineeringNoise reductionPhysicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Engine run-ups are part of the regular maintenance schedule at Vancouver International Airport. The noise generated by the run-ups propagates into neighboring communities, disturbing the residents. Active noise control is a potentially cost-effective alternative to passive methods, such as enclosures. Propeller aircraft generate low-frequency tonal noise that is highly compatible with active control. This paper presents a preliminary investigation of the feasibility and effectiveness of controlling run-up noise from propeller aircraft using local active control. Computer simulations for different configurations of multi-channel active-noise-control systems, aimed at reducing run-up noise in adjacent residential areas using a local-control strategy, were performed. These were based on an optimal configuration of a single-channel control system studied previously. The variations of the attenuation and amplification zones with the number of control channels, and with source/control-system geometry, were studied. Here, the aircraft was modeled using one or two sources, with monopole or multipole radiation patterns. Both free-field and half-space conditions were considered: for the configurations studied, results were similar in the two cases. In both cases, large triangular quiet zones, with local attenuations of 10 dB or more, were obtained when nine or more control channels were used. Increases of noise were predicted outside of these areas, but these were minimized as more control channels were employed. By combining predicted attenuations with measured noise spectra, noise levels after implementation of an active control system were estimated.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.287

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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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 designSimulation or modeling
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

Citations7
Published2003
Admission routes3
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicVehicle Noise and Vibration ControlFrench-language works237,207