Method for controlling boundary condition effects on the measurement of acoustic properties of small samples in tubes
Bibliographic record
Abstract
As standard ASTM E2611 reveals, the normal incidence sound transmission loss measured on a small sample in an acoustic tube is not only a property of the material but also strongly dependent on boundary conditions (generally unknown) and on the way the material is mounted. This article proposes an experimental method to control the effects of the lateral boundary conditions in an acoustic tube. The main objective is to deduce the properties of a "client element" (material sample) from the measured global acoustic properties of a patchwork composed by the "client material" and a known "host support." Three patchwork configurations have to be distinguished: patchworks with and without an impervious and rigid interface between the elements and patchworks composed by elements that cannot be identified as equivalent fluids. For each of these configurations, the use of a specific method based on the Mixing Rule Method (MRM) or on the Parallel Transfer Matrix Methods (P-TMM or dP-TMM) used in reverse way is proposed. Numerical and experimental validations are proposed in acoustic tubes on a convenient configuration: a material sample surrounded by an air ring. This configuration allows reducing the material elastic-frame behavior to leave a limp-frame behavior. The proposed methods allow removing the effect of the lateral air ring host surrounding the material. For homogeneous materials, the two methods based on MRM and dP-TMM give similar good results. For non-homogeneous materials or for materials that cannot be modeled as equivalent fluids, only the method based on dP-TMM gives good results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.000 | 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 teacher head, 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".