Seismic measurements in sand specimens with varying degrees of saturation using piezoelectric transducers
Bibliographic record
Abstract
Small-strain seismic measurements in sand specimens were undertaken in the laboratory using piezoelectric transducers. The measurements involved determining both constrained compression wave and shear wave velocities, V p and V s , respectively. The piezoelectric transducers were discs (PDs) for V p measurements and bender elements (BEs) for V s measurements. An instrumented triaxial chamber (ITC) was developed and associated support instrumentation was assembled to perform the seismic measurements. The same PDs and BEs were installed in a combined resonant column and torsional shear (RCTS) device. The soil tested in both devices was washed mortar sand. The sand was tested in dry, unsaturated, and saturated conditions in the ITC, while only dry sand was tested in the RCTS. Development, calibration, and operation of the PDs and BEs are discussed. Example waveforms are presented, which are associated with different stress levels, saturation conditions, and frequencies of excitation for P and S waves. A critical factor in performing successful measurements is the driving of each type of piezoelectric transducer at the optimum frequency, which depends on the effective confining pressure ([Formula: see text]), degree of saturation, and soil type. The excitation frequency used for PDs was found to be important when the sand specimens were at nearly or fully saturated conditions.
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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 | 0.000 | 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) | 0.001 | 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".