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Record W4415455497 · doi:10.3397/in_2025_1074280

Finite element modeling of metamaterial made of acoustic black hole profiles for achieving broadband sound absorption.

2025· article· en· W4415455497 on OpenAlex
Zacharie Laly, Raymond Panneton, Noureddine Atalla, Sebastian Ghinet, Kévin Verdière

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-CON proceedings · 2025
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsNational Research Council CanadaUniversité de Sherbrooke
Fundersnot available
KeywordsBroadbandRADIUSAttenuation coefficientAbsorption (acoustics)Noise reduction coefficientFinite element methodMetamaterialFrequency band

Abstract

fetched live from OpenAlex

To achieve broadband sound absorption, acoustic metamaterial composed of periodically arranged thin annular cavities, separated by rings and connected through a main central pore is studied using finite element method. The geometry of the main pore is varied by applying different decreasing hole profile functions. Each annular cavity has a thickness of 1 mm, and the radius of the rings decreases progressively from the inlet, following linear, exponential, quadratic and sinusoidal decay functions. Considering up to 40 annular cavities, each main pore profile results in a broad frequency band of sound absorption coefficient. The exponential pore profile exhibits five absorption peaks below 1200 Hz and an average absorption coefficient of about 0.9 above 2000 Hz. In contrast, the other pore profiles achieve an average sound absorption coefficient of about 0.98 above 1500 Hz. As the radius of the inlet ring decreases, the sound absorption coefficient and the frequency band decrease. The studied metamaterial is suitable for various applications aimed at reducing broadband noise.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.956

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 head0.022
GPT teacher head0.263
Teacher spread0.241 · 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