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Record W4403272275 · doi:10.3397/in_2024_4290

Harmonic acoustic pneumatic source (HAPS) to generate sound at very low-frequency

2024· article· en· W4403272275 on OpenAlexaff
Philippe Micheau, Pierre-Olivier Lajoie, Jean‐Christophe Chamard, Manuel Melon

Bibliographic record

VenueNOISE-CON proceedings · 2024
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsAcousticsHarmonicSound (geography)Computer sciencePhysicsEnvironmental science

Abstract

fetched live from OpenAlex

At very low frequency, the loudspeakers face technical issues (size, weight, energy consumption). An alternative to the electrodynamic loudspeaker is the Harmonic Acoustic Pneumatic Source (HAPS) demonstrated efficient in active tonal control. It comprises a high-pressure pneumatic air source, a rotating flow chopper, and an exhaust. The rotation of the flow chopper generates a pulsed flow which radiated noise out from the exhaust. An analytical model of the HAPS is presented to introduce the main challenge associated with its use at very low frequencies: having a high mean flow rate with a relatively small exhaust duct section. To overcome these challenge, a dedicated flexible tube (under light mean pressure) is added to the exhaust circuit to obtain a pulsating sphere activated by a HAPS. This configuration has been experimentally studied in a semi-anechoic room with two flexible tubes and without. The sound pressure level of the first harmonic at 1 meter range from 75 to 95 dB SPL (25 to 160 Hz, plenum pressure from 5 to 20 PSI). Thanks to fluid-structure interaction, the fundamental harmonic sound levels radiated by the compliant tube were free of jet noise. The drawback is the high harmonic distortion observed during the experiments.

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 score0.004
Threshold uncertainty score0.014

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.240
Teacher spread0.224 · 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
Published2024
Admission routes1
Has abstractyes

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Same venueNOISE-CON proceedingsSame topicAcoustic Wave Phenomena ResearchFrench-language works237,207