Numerical prediction of the broadband sound attenuation of a commercial earmuff: Impact of the cushion modeling
Bibliographic record
Abstract
Passive earmuffs are commonly used when the sound level cannot be reduced at the source. They are mainly characterized by their sound attenuation that can be either measured or simulated. In this work, the sound attenuation of a commercial earmuff is calculated using a finite element model from 100 Hz to 5 kHz. Emphasis is put on the foam-filled cushion which is the trickiest component to model because of its physical complexity. This multiphasic cushion is modeled in a simplified way as an equivalent solid, either isotropic or transverse isotropic in order to take into account the added transverse stiffness due to the bulging of the cushion polymeric sheath. The accuracy of these models is investigated by comparison with measurements. The insertion loss (IL) predicted with the isotropic cushion model is highly underestimated between 500 Hz and 2.5 kHz due to the presence of an unrealistic mode of transverse deformation. It is found that (1) neglecting the acoustic excitation on the cushion’s flanks of the isotropic model or (2) using the transverse isotropic cushion model significantly improves the simulated IL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".