A novel method for determining the small-strain shear modulus of soil using the bender elements technique
Bibliographic record
Abstract
Bender elements technique has become a popular tool for determining shear wave velocity, Vs, hence the small-strain shear modulus of soils, Gmax, thanks to its simplicity and nondestructive character among other advantages. Several methods were proposed to determine the first arrival of Vs. However, none of them can be widely adopted as a standard and there is still an uncertainty on the detection of the first arrival. In this study, bender elements tests were performed on lime-treated soil and both shear wave and compression wave velocities at various frequencies were measured. In-depth analysis showed that the S-wave received signal presents an identical travel time and opposite polarity compared with that of the S-wave components in P-wave received signal, especially at high frequency. From this observation, a novel interpretation method based on the comparison between the S-wave and P-wave received signals at high frequency is proposed. This method enables the determination of the arrival time of the S-wave objectively, avoiding a less reliable first arrival pick-up point. Furthermore, the “π-point” method and cross-correlation method were also employed and the obtained results agree well with those from the proposed method, indicating the accuracy and reliability of the latter. The effects of frequency on the shear wave velocity are also discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".