Influencia del origen y la mineralogía de las arenas en la resistencia a licuación Influence of sand origin and mineralogy on liquefaction resistance
Bibliographic record
Abstract
The available methods in the literature to assess liquefaction resistance of sands are based on studies using terrigenous sands with silica or quartzitic mineralogy. This is in part because terrigenous sands are the most abundant. However, there are other kinds of sands, in terms of origin, mineralogy and grain shape, for which their liquefaction susceptibility has not been studied in enough detail. This paper tries to fill this knowledge gap by presenting results of a detailed experimental program carried out to determine the liquefaction resistance of uncemented calcareous sand. This study involved mineralogical characterization, main index properties determination, critical state line, and undrained cyclic triaxial tests with isotropic consolidation on the calcareous sand. For comparison purposes, similar tests were performed on Ottawa standard silica sand. The results showed that the calcareous sands exhibited higher liquefaction resistance than silica sand, when tested under similar test conditions. Significant differences were also observed in terms of pore pressure generation and accumulation of axial strain during the undrained cyclic loading phase of the triaxial tests.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".