Dynamic response of a low plasticity silt deposit: comparison of in-situ and laboratory responses
Bibliographic record
Abstract
This study compares the in-situ dynamic response of a low plasticity silt deposit subjected to multidirectional loading from vibroseis shaking and controlled blasting to a suite of element-scale, cyclic laboratory test specimens. The agreement between excess pore pressures and simple shear strain relationships over a wide range in strains is remarkable. Slightly larger excess pore pressures observed in-situ are attributed to three-dimensional loading and pore pressure migration/redistribution in the shallower portions of the deposit. Noted differences in shear modulus, G, are attributed to strain rate effects, spatial variability in the in-situ stiffness, and hydraulic boundary conditions. The variation in in-situ G/Gmax follows the trend from torsional shear specimens up to 0.4% shear strain; larger strains in the silt deposit imposed by controlled blasting yielded a stiffer response than that from cyclic torsional shear and direct simple shear specimens due in part to field drainage for deeper portions of the deposit. The in-situ cyclic resistance ratio for the deeper portion of the deposit in which plane body waves could be assumed and for the selected excess pore pressure ratio criterion was larger than that of stress-controlled cyclic direct simple shear (CDSS) test specimens, despite the detrimental effect of multidirectional shaking in the field. The effect of strain history, spatial variability, and drainage boundary conditions to drive differences between the in-situ and laboratory test specimens is identified.
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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) | 0.002 | 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".