Interfacial effects in underwater acoustic panel measurements
Bibliographic record
Abstract
Underwater acoustic panel measurements were conducted on single layers of rubber or metal, and on rubber/metal bilayers that had been fabricated using various adhesives or attachment methods. Reflection and transmission measurements were carried out on submerged panels using a parametric array source. It was found that the condition of the various interfaces in the system (water/rubber, water/metal, or rubber/metal) had a dominant effect on the measured acoustic properties. Single layer (metal or rubber) panels with smooth surfaces behaved in accordance with theoretical predictions, but panels with even a small amount of surface roughness did not. This was attributed to a non-ideal water/sample interface, most likely due to the presence of air bubbles. The effect of various surface treatments on the acoustic behaviour of the panels was investigated. Different adhesion methods for fabricating aluminum/rubber bilayers were tested for their practicality and effects on underwater acoustic properties. Nitrile butadiene rubber and aluminum panels were adhered to one another using pressure sensitive adhesive, contact cement, banded duct tape, or epoxy, and tested in transmission and reflection. The results were strongly dependent on adhesion method, with only one method (epoxy cured under 15 psi pressure) giving results that matched theoretical predictions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".