Acoustic Characterization of Inhomogenous Layers using Finite Element Method
Bibliographic record
Abstract
This study presents a finite element approach to estimate acoustic parameters of layers of arbitrary compositions using 2D and 3D models. In this approach the resonance frequency of a layer to be investigated is found by exciting the layer with plane waves and studying the reflected and transmitted sound pressure from the layer. Compressional and shear modes can be excited separately by varying the angle of incidence. A script for generating inhomogeneous layers with randomly distributed inclusions of arbitrary shape and size was developed for this study. A Matlab application was built for processing the result and comparison with analytical calculations. The 2D and 3D models were validated by comparing derived acoustic parameters of known materials with no more than 0.06% deviation from expected values. Estimated parameters for a layer of gold with 10.6% volume fraction of spherical inclusions of voids of 3 µm and 5 µm diameter was found to range from 2540 m/s to 2652 m/s for compressional sound speed and from 1039 m/s to 1067 for shear speed of sound.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".