Combined Time and Frequency Domain Approach to the Interpretation of Bender-Element Tests on Sand
Bibliographic record
Abstract
Abstract Shear wave velocities are obtained from bender-element tests on laboratory specimens by analyzing the trigger and response signals. The response signal is a highly distorted translation of the trigger signal, obscuring the identification of the shear wave arrival. This has led to the publication of many criteria to guide subjective decisions on the selection of trigger waveform and frequency and of applicable interpretation methods. Current methods of interpretation result in determination of either the group or phase velocity. As soil and bender-element responses are dispersive, and as the group velocity is only valid in non-dispersive systems, the phase velocity should be measured. A combined time and frequency domain method is presented to allow interpretation of the phase velocity, minimizing subjective input to the interpretation. The method is first demonstrated using simplified synthetic signals and is then applied to laboratory test data. The reproducibility of the results is demonstrated from measurements on ten triaxial specimens of saturated Fraser River sand. The group velocities are shown to be very sensitive to dispersion, not reproducible, and contingent on the selected frequency window, whereas the phase velocities are considerably more repeatable. The combined time and frequency domain method results in the interpretation of a phase velocity using only measured parameters.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".