Exploring the effect of bed thickness on liquefaction of sediments overridden by landslides
Bibliographic record
Abstract
As the consequences of global climate change become increasingly apparent, the ability to create accurate landslide runout analyses has become critical. These analyses can provide estimates of the potential volume and reach of future landslides and may be used to inform hazard awareness, risk management, and the design of mitigation and emergency response measures. A key uncertainty within landslide hazard assessment relates to the behaviour and possible entrainment of the sediment it travels over, which may affect the distal reach and volume of the slide. In this study we explore the extreme case of a highspeed landslide overriding loose saturated valley floor sediments vulnerable to static liquefaction; in particular, how static liquefaction progresses through the bed when the sediments are overridden and how the depth of liquefiable sediment available affects whether and how liquefaction occurs.A static liquefaction hazard may be posed when a loose saturated layer of sand is located at the base of a landslide-prone slope so that a contractive soil is both fully saturated and in reach of a shear trigger (i.e., the landslide). This scenario was reproduced in the Queen’s landslide flume using horizontal liquefiable beds of saturated fine sand 2 m in width, 4 m in length, and at various thicknesses, located at the bottom of the inclined portion of the flume. Landslides of 700 kg of saturated granular material were then released from the top of a 6.5 m long slope inclined at 30 degrees to impact the beds at speeds of up to 6 m/s. Behaviour of the sand beds upon impact was captured using ultrahigh speed imaging of the landslide and bed profiles, a Blickfeld LiDAR sensor positioned opposite to the landslide to capture point cloud scans of the slide, and a linear array of porewater pressure sensors within the sand bed. Experiments comparing different liquefiable bed thicknesses to height of slide ratios will be presented as we explore the effect of bed depth on liquefaction susceptibility, extent of liquefaction, and the rate of excess porewater pressure generation, dissipation, and deformation within the sand bed during impact.
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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".