Compression and shear wave propagation in cemented-sand specimens
Bibliographic record
Abstract
Ultrasonic and bender element tests in the laboratory are typically used to measure elastic modulus and damping ratio. However, interpretation of the results is challenging for a variety of reasons, including the influence of experimental details, geometrical effects and the analytical techniques used for data processing. It is therefore convenient to cross-check results by performing several independent measurements. Three different types of measurements were performed on cemented-sand specimens. Longitudinal waves or constrained compressional waves in a cylindrical specimen were generated in a high-frequency range (20–70 kHz) using a newly designed transducer interface. Full dynamic characterisation was made possible by independent measurement of the transducer response. Pure unconstrained compressional waves or simply compression waves were measured in the same specimens with high-frequency transducers. The shear modulus was computed and used to predict the arrival of shear waves on independent bender element measurements. The predicted arrival was close to first-break estimates, and bender measurements were therefore confidently employed to track cement curing effects on a different set of specimens. The specimen frequency response function obtained from the longitudinal wave measurements was examined in detail and damping ratios were estimated for the compression vibration modes in a rod.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".