Seismic liquefaction, lateral spreading, and flow slides: a numerical investigation into void redistribution
Bibliographic record
Abstract
Experience from past earthquakes indicates that seismically induced large lateral spreads and flow slides in alluvial sand deposits have taken place in coastal and river areas in many parts of the world. The ground slope in these slides was often not very steep, gentler than a few percent. Recent research indicates that the presence of low-permeability silt or clay sublayers within the sand deposits is responsible for this behaviour. Such layers form a barrier to upward flow of water associated with earthquake-generated pore pressures. This causes an accumulation of pore water at the base of the layers, resulting in greatly reduced strength and possible slope instability. This paper uses an effective stress coupled stress-flow dynamic analyses procedure to demonstrate the effects of a low-permeability barrier layer on ground deformations from an earthquake event. The analyses show that an expansion zone develops at the base of barrier layers in stratified soil deposits under seismic loading which can greatly reduce shear strength and result in large deformations and flow failure. Without such a layer or layers, the slope may undergo significant displacements, but not a flow slide. Slopes with a barrier layer can be stabilized by drains.Key words: liquefaction, lateral spreads, stratification, flow failure, dynamic analysis, UBCSAND model, drain.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".