MétaCan
Menu
Back to cohort
Record W4401712694 · doi:10.1121/2.0001929

Sound attenuation performance at high sound pressure level of micro-perforated panel sound absorber with embedded resistive screen

2024· article· en· W4401712694 on OpenAlexaff
Zacharie Laly, Noureddine Atalla

Bibliographic record

VenueProceedings of meetings on acoustics · 2024
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
FundersAustralian Government
KeywordsAcousticsSound (geography)Acoustic attenuationAttenuationSound pressureResistive touchscreenSound powerMaterials scienceAcoustic source localizationSound intensity probePhysicsEngineeringOpticsCritical distanceElectrical engineering

Abstract

fetched live from OpenAlex

To enlarge the sound absorption frequency band of micro perforated panel (MPP) absorbers, a composite sound absorber made of an MPP, an air cavity with embedded resistive screens and a rigid back plate is proposed and studied at high sound pressure level (SPL).The sound absorption coefficient predicted theoretically is compared with the experimental measurement at 150 dB and a good agreement is obtained.With one layer of resistive screen within the air cavity, the sound absorption coefficient is significantly improved over a large frequency band and remains almost identical with respect to the SPL compared to a classical MPP absorber whose sound absorption frequency band is narrow with a resonant peak that varies with the SPL.When two resistive screens layers are embedded within the air cavity, the absorption frequency band is further improved.The impacts of the perforation ratio of the MPP on the sound absorption performance are illustrated.A sensitivity analysis shows that the resistance per unit area of the screen affects the acoustic properties of the absorber at low SPL while at high SPL, the acoustic properties are mainly controlled by the perforation ratio of the MPP and the acoustic orifice Mach number.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.257
Teacher spread0.205 · 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 teacher head, not a consensus.

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

Explore more

Same venueProceedings of meetings on acousticsSame topicAcoustic Wave Phenomena ResearchFrench-language works237,207