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Record W4389540829 · doi:10.17118/11143/21114

Harmonic acoustic pneumatic source (HAPS) as a narrow bandwidth acousticloudspeaker

2023· article· en· W4389540829 on OpenAlexaff
Alexandre Schiavini, Philippe Micheau, Pierre Grandjean, Gwénaël Gabard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsLoudspeakerAcousticsBandwidth (computing)HarmonicComputer sciencePhysicsTelecommunications

Abstract

fetched live from OpenAlex

During takeoff, the harmonic noise of the turbofan is the main acoustic nuisance for people near airports. Much research has been done to achieve active noise control of turbofans with loudspeakers or piezo actuators as noise suppression sources. However, the required fragility, and weight and volume penalty make them unsuitable for engine nacelle applications. On the other hand, electro-pneumatic sound sources (sirens or air modulators) are good candidates for generating the required high noise control sound pressure level, but they are not designed for active noise control applications. Therefore, an alternative solution, called the Harmonic Acoustic Pneumatic Source (HAPS), has been designed to generate a high harmonic noise level controllable in amplitude, phase and frequency. The specificity of the HAPS is to use a flow chopper to generate a pulsed jet at a given frequency and a servo-valve to control its amplitude.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.247
Teacher spread0.230 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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