Recovery of small-strain stiffness following blast-induced liquefaction based on shear wave velocity measurements
Bibliographic record
Abstract
Changes in soil fabric following liquefaction have been studied using various in situ methods that often return inconclusive or conflicting observations. The time–rate variation of stiffness, when observed, is usually not evaluated over significant periods of time, limiting investigations about aging in post-liquefaction regain of stiffness. Even more uncommon is the application of geophysical techniques to evaluate changes in shear wave velocity (V S) as a proxy for small-strain stiffness. This study uses controlled blasting to examine long-term post-liquefaction regain of stiffness following multiple blast events. The multi-channel analysis of surface waves (MASW) technique was used to observe changes in V S of aged deposits at a test site in South Carolina. Blast-induced liquefaction of the target liquefiable layer resulted in significant reduction to its initial small-strain stiffness owing to the destruction of the aged soil fabric. The time-rate variation in V S indicated that the initial small-strain stiffness was not re-established over many months following liquefaction. Following a second blast event, the small-strain stiffness reduced again, but recovered more quickly, similar to previously reported observations of young sand deposits. This study provides a significant basis for interpreting in situ body and surface wave measurements of aged and young sand deposits densified using blast liquefaction.
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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".