Generation of broadband airborne ultrasound using an Harmonic Acoustic Pneumatic Source
Bibliographic record
Abstract
This paper presents a new type of airborne transducer for generating broadband ultrasound with a high Sound Pressure Level (SPL). The concept is based on the Harmonic Acoustic Pneumatic Source (HAPS) that uses pressurized air in conjunction with a flow chopper made up of a rotating cage with slots connected to a specific exhaust. The fundamental frequency depends on the number of slots and the rotation speed of the cage. An analytical model of the HAPS coupled with a numerical model of the exhaust is used to predict the radiated acoustic pressure and to estimate the influence of dimensional parameters on pressure level generated by the source. Experiments are conducted with two cages: one with one slot in order to generate pulses periodically and one with 122 slots to generate periodic sound. The level of sound pressure is measured as a function of distance (0.004 to 0.5 m), the cage rotation (up to 11 krpm) and directivity (0 to 90°). For the fundamental frequency at 22 kHz, the maximum SPL of 150 dB (632 Pa rms) is /measured at 0.004 m, and decreases to 122 dB (35 Pa rms) at 0.5 m. At 0.5 m, the second and third harmonics can generate a SPL equal or greater than 115 dB above 22 kHz and up to 66 kHz. Discrepancies between the experiments results and numerical model are observed in terms of SPL, directivity and in-axis pressure.
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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) | 0.000 | 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) | 0.001 | 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".