Influence of silt size and content on liquefaction behavior of sands
Bibliographic record
Abstract
This study investigates the fines content influence on liquefaction potential of a single base sand mixed with three different essentially nonplastic silts through strain-controlled monotonic undrained triaxial compression tests. Confining stress (30 kPa) and deposition method (dry funnel deposition) were kept the same, while fines content was varied, to solely focus on how different silts and their contents influence the undrained response of the sand under comparable conditions. It was found that if the mean grain diameter ratio (D 50-sand /d 50-silt ) of the sand grains to silt grains is sufficiently small, the liquefaction potential of the sand increases steadily with increasing fines content for the studied range (0%–20%). As D 50-sand /d 50-silt increases, the liquefaction potential of the silty sand might actually be less than the liquefaction potential of the clean sand. Test results also revealed that commonly used comparison bases (i.e., void ratio, intergranular void ratio, relative density) are not sufficient for assessing the influence of fines on liquefaction potential of silty sands. Finally, relative size of the silt grains should also be considered in geotechnical engineering practice in addition to content and plasticity of fines to characterize the influence of silt on liquefaction potential of sands.
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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 | 0.001 |
| 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".