Transfer matrix modeling and experimental validation of cellular porous material with resonant inclusions
Bibliographic record
Abstract
Porous materials are widely used for improving sound absorption and sound transmission loss of vibrating structures. However, their efficiency is limited to medium and high frequencies of sound. A solution for improving their low frequency behavior while keeping an acceptable thickness is to embed resonant structures such as Helmholtz resonators (HRs). This work investigates the absorption and transmission acoustic performances of a cellular porous material with a two-dimensional periodic arrangement of HR inclusions. A low frequency model of a resonant periodic unit cell based on the parallel transfer matrix method is presented. The model is validated by comparison with impedance tube measurements and simulations based on both the finite element method and a homogenization based model. At the HR resonance frequency (i) the transmission loss is greatly improved and (ii) the sound absorption of the foam can be either decreased or improved depending on the HR tuning frequency and on the thickness and properties of the host foam. Finally, the diffuse field sound absorption and diffuse field sound transmission loss performance of a 2.6 m(2) resonant cellular material are measured. It is shown that the improvements observed at the Helmholtz resonant frequency on a single cell are confirmed at a larger scale.
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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 | 0.001 | 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".