A simple method to optimize the sound package in a double wall structure.
Bibliographic record
Abstract
The acoustic contributions to the transmission loss of an unbounded sound package in a double panel structure are investigated. For this purpose, a simple analytic expression of the normal incidence sound transmission loss of the double panel structure is proposed in terms of three main contributions: sound transmission loss of the panels, sound transmission loss of the blanket, and sound absorption due to multiple reflections inside the structure. It is shown that (i) at high frequencies, the transmission loss contribution of the blanket is preponderant compared to the absorption contributions;(ii) at the cavity resonance frequencies, the absorption contribution allows to attenuate the dips of insulation; and (iii) at medium and low frequencies, when the absorption performance of the porous layer is poor, the absorption contributions in the air-gaps can decrease the sound transmission loss performance of the double panel. The proposed methodology can also be used to estimate, from classical impedance tube measurements of the sound package only, the transmission loss of the whole double wall configuration. Testing the influence of various sound packages in a given double panel structure thus becomes quick and much less expensive compared to classical tests.
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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) | 0.001 | 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) | 0.005 | 0.002 |
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".