Sound attenuation analysis of a honeycomb structure with extended necks
Bibliographic record
Abstract
In this paper, a honeycomb structure metamaterial consisting of 95 necks that are attached to the perforated top panel is presented and its sound absorption coefficient and transmission loss are investigated using the finite element method. Helmholtz resonators are therefore created by each honeycomb cell (cavity) and the attached neck, which is protruding within each cell. The structure has therefore a high bending stiffness due to the honeycomb mechanical performance and constitutes a sound absorber based on the parallel assembly of multiple Helmholtz resonators. This study demonstrates the importance of properly designing the diameter and the length of each neck to create a broadband sound absorption. One resonant sound absorption peak is observed when all the necks are identical, and two absorption peaks are obtained using two different sets of neck parameters. When the number of different necks increases, the sound absorption frequency band improves and when the parameters of all the necks are different, resulting in a parallel assembly of 95 different Helmholtz resonators, the sound absorption frequency band broadens. The material design studied in this paper can be useful in various applications where available space is limited and high mechanical stiffness and noise reduction are required in one structural element.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 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".