A finite element model to predict the double hearing protector effect on an in-house acoustic test fixture
Bibliographic record
Abstract
The sound attenuation of double hearing protectors (DHPs), earplugs combined with earmuffs, generally falls short of the sum of each single protector's attenuation when used independently. This phenomenon, referred to as the DHP effect, is found to be related to structure-borne sound transmission involving the outer ear and can also be observed on acoustic test fixtures (ATFs). At present, it still remains not fully understood, and no available model can help demonstrate the associated sound transmission mechanisms. In this work, a finite element model is proposed to study the DHP effect on an ATF between 100 Hz and 5 kHz. Power balances are calculated with selected configurations of the ATF in order to (i) quantify the contribution of each sound path, and study the effects of (ii) the artificial skin and (iii) acoustic excitation on the ATF exterior boundaries. The DHP effect is shown to originate from the structure-borne sound power injected from the ATF boundaries and/or earmuff cushion. The important influence of earcanal wall vibration is highlighted when the skin is accounted for. The simulation results allow for gaining more insight into the sound transmission through a DHP/ATF system.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".