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Record W1931726037

Finite element analysis of an earmuff-earcanal system

2007· article· en· W1931726037 on OpenAlexaffvenue
Mahborbeh Khani, R. Kechroud, Azzeddine Soulaïmani

Bibliographic record

VenueCanadian acoustics · 2007
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsFinite element methodAcousticsDisplacement (psychology)AttenuationMechanicsDiscretizationSound pressurePhysicsStiffness matrixMathematical analysisMathematicsOptics
DOInot available

Abstract

fetched live from OpenAlex

The finite element model (FEM) of an earmuff-earcanal coupled structure-acoustic-cavity system to predict the level of protection for the wearer is discussed. The discretization of the pressure-wave equation by the finite element method leads to differential system of equations depending on fluid mass, stiffness matrix, and nodal pressure vector. The displacement of the structure coincides with the displacement of the acoustic particle while the dynamic equilibrium condition requires the normal force produced by the vibrating structure at the interface. The air cavity created within the ear-cup extends into the ear-canal up to the eardrum which is represented by a specific impedance. The predicted FEM attenuation provided by the earmuff is equal to 12.00 dB which is equal to 12.6 dB. The attenuation of the eanmuff is found to be weak around the first resonant 140 Hz of the coupled system.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations1
Published2007
Admission routes2
Has abstractyes

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