Numerical modeling of liquefaction and comparison with centrifuge tests
Bibliographic record
Abstract
The prediction of liquefaction and resulting displacements is a major concern for earth structures located in regions of moderate to high seismicity. Conventional procedures used to assess liquefaction commonly predict the triggering of liquefaction to depths of 50 m or more. Remediation to prevent or curtail liquefaction at these depths can be very expensive. Field experience during past earthquakes indicates that liquefaction has mainly occurred at depths less than about 15 m, and some recent dynamic centrifuge model testing initially appeared to confirm a depth or confining-stress limitation on the occurrence of liquefaction. Such a limitation on liquefaction could greatly reduce remediation costs. In this paper an effective stress numerical modeling procedure is used to assess these centrifuge tests. The results indicate that a lack of complete saturation and densification at depth arising from the application of the high-acceleration field are largely responsible for the apparent limitation on liquefaction at depth observed in some centrifuge tests.Key words: liquefaction, dynamic centrifuge modeling, numerical modeling, depth limitation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".