<i>Review / Sythèse</i> Nonlinear acoustic applications for material characterization: A review
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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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.015 |
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".