Time-Domain Numerical Investigation to Assess Noise Reduction Allowed by a Non-Linear Passive Earplug Facing Impulse Noises.
Bibliographic record
Abstract
To protect the hearing against high-level impulse noises, non-linear passive earplugs (NLPE) might be employed. Unlike conventional passive protectors, these devices provide an increasing peak amplitude attenuation with the impulse noise level thanks to filters made of one or more small orifices. To evaluate these protectors’ performances, empirical studies were previously conducted using acoustic test fixtures. However, these evaluations required a specific and expensive protocol. Thus, a new approach based on the Finite Element Method (FEM) was used to model a NLPE inserted in the ear canal and facing a 130 dB-peak and a 150 dB-peak impulse wave. The FEM model acoustic pressure in the ear canal corroborates the pressure evaluated experimentally. This approach provides a promising avenue for further optimization of these hearing protectors, while limiting the high cost of experimental evaluations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
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 teacher head, 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".