Numerical design of Helmholtz resonators with multiple necks for multi-tonal noise control
Bibliographic record
Abstract
The reduction of multi-tonal noise at multiple frequencies simultaneously is a challenge in many industrial fields. Different solutions such as metamaterials consisting of periodic Helmholtz resonators embedded into a porous layer have been studied in the literature. Generally, a classical resonator made of a cavity connected to a neck provides only one resonant transmission loss peak. In this study, a design of acoustic metamaterials is proposed numerically using the finite element method for multi-tonal noise reduction. The resonator is made of multiple necks extended into the cavity and is periodically distributed within a porous material. The cylindrical global cavity of the resonator is partitioned into several sub-cavities, which are separated from one another by a rigid wall, and each sub-cavity is connected to one neck. Helmholtz resonators with 2, 3, 4, and 5 necks are presented, they exhibit multiple resonance transmission loss peaks which correspond respectively to the number of the resonator necks. The proposed acoustic metamaterial designs can be used to reduce multi-total noise at several frequencies simultaneously.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".