Axisymmetric versus three-dimensional finite element models for predicting the attenuation of earplugs in rigid walled ear canals
Bibliographic record
Abstract
The axisymmetric hypothesis of the earplug-ear canal system geometry is commonly used. The validity of this hypothesis is investigated numerically in the case of a simplified configuration where the system is embedded in a rigid baffle and for fixed boundary conditions on the earplug lateral walls. This investigation is discussed for both individual and averaged insertion loss predictions of molded silicon earplugs. The insertion losses of 15 earplug-ear canal systems with realistic geometries are calculated using three-dimensional (3D) finite element models and compared with the insertion losses provided by two-dimensional equivalent axisymmetric finite element models using 6 different geometry reconstruction methods [all the models are solved using COMSOL Multiphysics (COMSOL, Sweden)]. These methods are then compared in order to find the most reliable ones in terms of insertion loss predictions in this simplified configuration. Two methods have emerged: The usage of a variable cross section (with the same area values as the 3D case) or the usage of a constant cross section (with the same length and volume as the 3D case).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".