Low frequency finite element models of the acoustical behavior of earmuffs
Bibliographic record
Abstract
This paper compares different approaches to model the vibroacoustic behavior of earmuffs at low frequency and investigates their accuracy by comparison with objective insertion loss measurements recently carried out by Boyer et al. [(2014). Appl. Acoust. 83, 76-85]. Two models based on the finite element (FE) method where the cushion is either modeled as a spring foundation (SF) or as an equivalent solid (ES), and the well-known lumped parameters model (LPM) are investigated. Modeling results show that: (i) all modeling strategies are in good agreement with measurements, providing that the characterization of the cushion equivalent mechanical properties are performed with great care and as close as possible to in situ loading, boundary, and environmental conditions and that the frequency dependence of the mechanical properties is taken into account, (ii) the LPM is the most simple modeling strategy, but the air volume enclosed by the earmuff must be correctly estimated, which is not as straightforward as it may seem, (iii) similar results are obtained with the SF and the ES FE-models of the cushion, but the SF should be preferred to predict the earmuff acoustic response at low frequency since it requires less parameters and a less complex characterization procedure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".