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Record W4408914621 · doi:10.3397/1/37737

Case study: Sub-metamaterials for Broadband Aircraft Noise Reduction Across Low and High Frequencies

2025· article· en· W4408914621 on OpenAlex
Tenon Charly Kone, Sebastian Ghinet, Raymond Panneton, Anant Grewal

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNoise Control Engineering Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de SherbrookeNational Research Council Canada
Fundersnot available
KeywordsBroadbandMetamaterialAcousticsReduction (mathematics)Noise reductionNoise (video)PhysicsTelecommunicationsEngineeringComputer scienceOpticsMathematicsGeometry

Abstract

fetched live from OpenAlex

Controlling broadband noise across the entire frequency spectrum, from low to high frequencies, poses a significant challenge for the aerospace, transportation, and construction industries. Recent research has primarily focused on low-frequency noise control solutions using acoustic metamaterials, but these materials are often limited by their narrow-band resonances. This paper addresses this limitation by presenting a novel sub-metamaterial system that broadens the resonance frequency band from low to high frequencies through a parallel assembly of sub-metamaterials. The proposed system comprises an arrangement of structured metamaterials and Helmholtz Resonators embedded in a layer of glass fiber. By meticulously grouping individual resonant frequencies, this assembly effectively attenuates noise across the desired frequency range. Our research demonstrates promising potential for significant noise reduction within practical constraints, contributing to the development of durable solutions for aircraft noise mitigation over a broad frequency spectrum.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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