Application of the Surface Wave Survey Method on Multi-Scale Engineering Problems: Laboratory and Field Testing Case Studies
Bibliographic record
Abstract
Abstract The geometric dispersion of surface waves offers the feature to infer the properties of a medium. The surface wave survey method is under continuous evolution and its applications include the noninvasive characterization of a medium at a small scale and the earthquake geotechnical survey at a large scale. Despite the significant difference in scales, these applications generally utilize the propagation of the surface waves along the boundary of a layered medium. This paper discusses standard steps involved in surface wave surveys. Two application case studies are conducted and presented in detail. In the small scale laboratory application case, a nondestructive testing (NDT) methodology is proposed for the coating investigation using laser interferometric measurements of surface waves. In the large scale field application, an accelerometer-based passive surface wave survey is designed for earthquake geotechnical engineering site characterization. Finally, recommendations for practical application of surface waves in multi-scale engineering problems are presented.
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How this classification was reachedexpand
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".