Estimating sound absorption coefficient under various sound pressure fields by combining an automated test bench to sound field reproduction and advanced post-processing techniques
Bibliographic record
Abstract
The absorption coefficient of sound absorbing materials is usually obtained via impedance tube or reverberant room measurements. While impedance tube tests are restricted to normal incidence on small samples, reverberant room tests provide diffuse field absorption but require large samples and can result in overestimated absorption coefficients. This work investigates alternative methods estimating material’s absorption coefficient under oblique plane wave or diffuse field incidence. A sound field reproduction approach was previously proposed. It allows estimating the absorption coefficient of absorbing materials under a synthetized acoustic field. It involves a virtual monopole array and two microphones above the materials. It shows good agreement with Transfer Matrix Method (TMM) simulations and needs smaller samples than the reverberant room method. It is closer to actual mounting conditions than the standard techniques and does not require a specific room. No overestimation of the absorption coefficient is observed. However, below 400 Hz, results are unreliable, attributed to measurements uncertainties and to the simplified spherical wave model above a locally reacting material used to calculate the sound reflection coefficient. This paper aims at circumventing these limitations by using (i) an automated test bench reducing measurement uncertainties, (ii) an improved sound source and, (iii) a more general propagation model, namely Allard’s model, which is inverted to identify the materials’ complex density and wavenumber. Those properties are then used to calculate the diffuse field or oblique plane wave sound absorption coefficients based on two techniques. The first one relies on plane wave sound reflection coefficients. The second one uses a virtual sound field reproduction technique combined with a power definition for the absorption coefficient. Tests are conducted on five different materials in a semi-anechoic room and the two proposed approaches are compared with impedance tube and small cabin measurements. The results obtained are discussed along with experimental uncertainties.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".