Attenuation of dual hearing protection: Measurements and finite-element modeling
Bibliographic record
Abstract
In extremely noisy environments, it is normally recommended to use a combination of earplug and earmuff, denoted here as a dual protection, to protect workers from the excessive noise. Unfortunately, it has been shown repeatedly that the attenuation values obtained with the dual protection are generally less than the sum of the individual earplug and earmuff attenuation values. In the literature, this is generally explained by the bone conduction path and the coupling between the earplug and the earmuff. However, there is much less work devoted to examining in detail the coupling between the earplug and the earmuff. In this work, experimental results on human subjects and on an artificial text fixture are collected using REAT and MIRE procedures for different combinations of earmuffs and earplugs. Additionally, a finite-element model is used to investigate the physics of the problem and to better understand the nature of the coupling between the earplug and the earmuff when used in a dual configuration. Results from the experimental procedures as well as from the FE model are presented and discussed. These results clearly illustrate the importance of the coupling between the earplug and the earmuff when used in combination.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".