An ultrasonic array technique for material characterization of plate samples
Bibliographic record
Abstract
An ultrasonic system with a linear array for characterization of a layered specimen placed in immersion liquid parallel to the aperture of the array is considered. To estimate the longitudinal and transverse wave velocities as well as the thickness and density of the specimen, it is proposed to decompose the spatio-temporal data recorded by the array in a spectrum of plane pulse waves. Based on fitting the developed wave model of the system to the experimental data, it is shown that the relative delays and amplitudes of the spectral responses can be used for the estimation of the velocities and thickness of the layer and its density. The distortions of the plane wave spectrum caused by the spatial discretization of the array data are considered. It is proposed to suppress these distortions using individual interpolating processing of the received pulses separated in the spatio-temporal domain. The developed technique is experimentally verified on a fused quartz plate evaluated with a 17-MHz linear array. The relative reproducibility of the estimation is found to be 0.11% in the longitudinal wave velocity and thickness of the plate, and 0.5% and 5% in the transverse wave velocity and the density, respectively.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".