Investigations of an impedance tube technique to determine the transmission loss of materials under angular incidence
Bibliographic record
Abstract
The most polular technique for transmission loss characterization of porous materials is undoubtedly the impedance tube method based on the transfer matrix method (described in ASTM E2611) which is valid for frequencies of a few kilo hertz, depending on the tube's size. A mono dimensional harmonic plane wave is created at one tube's extremity ; this wave propagates inside the tube and is partially transmitted through an absorbing material to the opposite side of the tube. Using proper boundary conditions and measuring the sound pressure yields to the estimation of the transmission loss after a few algebraic manipulations. All measurement systems developed until now are based on a normal sound incidence. Yet, some modeling methods used for these materials are based on excitations with variable incidence angle and thus the validation of the developed models requires to use a facility system for which the characterization can be done using a variable wave incident angle ont he material. The work porposed here details the design of such an experimental system. This system is based on a new design of the classical impedance tube : a numerical study is carried out to identify the range of validity of the proposed technique. The possibilities that this new system offers as well as its limits in terms of incident angle or frequency are illustrated on specific samples.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".