<i>Review / Sythèse</i> Nonlinear acoustic applications for material characterization: A review
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Bibliographic record
Abstract
The nonlinear acoustic applications for material characterization are reviewed. The general theoretical analysis of the effects of nonlinearity, dissipation, dispersion, and diffraction on intense acoustic-wave propagation is given. Acoustic nonlinear parameters and their determination methods are introduced. The investigations of nonlinear acoustic applications for solid material evaluation are discussed for different levels of disruption, from asymmetry of lattice structure and dislocation in crystals to disbonds and cracks in engineering materials. The experimental methods involved in these investigations are also considered. The techniques used for nonlinear acoustic imaging are divided into two categories, concerned with resolution improvement by using higher harmonics, and nonlinear parametric imaging. The nonlinear acoustic applications in biomedical imaging, acoustic microscopy, and nonlinear nondestructive evaluation are presented. Finally, the issues that need further investigations in this area are discussed. PACS Nos.: 43.25, 62.65, 62.20M
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it