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Record W2801889462

Design of active Multiple-degrees-of-freedom electroacoustic resonators for use as broadband sound absorbers

2017· article· en· W2801889462 on OpenAlexaff
Hervé Lissek, Etienne Rivet, Sami Karkar, Romain Boulandet

Bibliographic record

VenueInfoscience (Ecole Polytechnique Fédérale de Lausanne) · 2017
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsResonatorLoudspeakerAcousticsAcoustic impedanceElectrical impedanceMicrophoneTransfer functionBroadbandImpedance controlController (irrigation)Noise controlDegrees of freedom (physics and chemistry)Computer scienceNoise reductionEngineeringElectronic engineeringElectrical engineeringPhysicsTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

We present a novel control method achieving stable multiple-degrees-of-freedom electroacoustic resonators. Such broadband absorbers, composed of a feedback-controlled electrodynamic loudspeaker, have many practical applications to real-world acoustic engineering problems, such as low-frequency industrial noise reduction in the range of [20 - 200 Hz]. The proposed control architecture combines a conventional microphone-based feedback control loop and a current-driven direct acoustic impedance control scheme, proven to perform optimally in recently reported acoustic impedance synthesis methods. This paper presents a methodology for designing the transfer function to be implemented in the controller, after specifying a target multiple-degree-of-freedom acoustic resonator impedance. Numerical simulations presents the expected acoustic performances, confirmed by experimental assessments in an impedance tube.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.043
GPT teacher head0.295
Teacher spread0.251 · 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
Published2017
Admission routes1
Has abstractyes

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