Periodic resonance effect for the design of low frequency acoustic absorbers
Bibliographic record
Abstract
This presentation examines a perforated resonant material, in which the principal perforations comprise a network of periodically spaced dead-end pores. This material can show good sound absorption at low frequencies, particularly given its relatively small thickness. In a recent study, this kind of material was modeled by an effective fluid approach which allowed low frequency approximations. At low frequency, it was shown that the periodic array of dead-end pores increases the effective compressibility without modifying the effective dynamic density. Thereby, the resonance frequency of the material is reduced in a significant way, as is the frequency of the first sound absorption peak. Moreover, a bandgap effect occurs at high frequency for the sound transmission problem. This study suggested a new concept of micro-structure for designing low-frequency resonant acoustic absorbers. A transfer matrix approach is now proposed to model and optimize such a concept. Prototypes have been made with 3D printing and tested in an acoustic tube for sound absorption and sound transmission loss. The resonant periodicity effects have been observed, and the measurements compare well with the predictions of the transfer matrix model. Finally, an optimization of the microstructure is proposed.
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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) | 0.001 | 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".