Ultrasonic propagation across a thin layer between two bulk media: Theory, computer simulation and experiment.
Bibliographic record
Abstract
This thesis describes the changes in the reflected and transmitted acoustic waves due to the addition of a thin layer (thickness much less than an acoustic wavelength) between two half-spaces of material. The restriction of the thin layer allows one to combine perturbation methods with the standard fully bonded boundary conditions at each interface and derive a set of equations where one no longer is concerned with the acoustic waves internal to the thin layer. This approach allows one to further examine the cases of a nonlinear thin layer, an anisotropic thin layer, and a thin layer with combined anisotropy and nonlinearity. A simulation is created to explore the various combinations of materials for the half-spaces and thin layers. In the simulation it is found that the case of half-spaces made with identical materials presents the most accurate results, and creates significant changes in the reflected and transmitted acoustic waves. The addition of anisotropy and nonlinearity also creates significant changes in certain acoustic polarizations. Finally, a qualitative experimental verification is attempted for the specific case of two identical half-spaces using a common adhesive, and anisotropic material for the thin layer. The experiment is found to yield qualitatively similar results to what is predicted by the simulation.Dept. of Physics. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .S23. Source: Masters Abstracts International, Volume: 42-03, page: 0950. Adviser: R. Gr. Maev. Thesis (M.Sc.)--University of Windsor (Canada), 2003.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".