Wave Generation Across a Continuum of Landslide Conditions From the Collapse of Partially Submerged to Fully Submerged Granular Columns
Bibliographic record
Abstract
Abstract Landslide generated tsunamis are a primary natural hazard to coastal communities and infrastructure, but the present state of knowledge is limited to the specific details of momentum transfer from the landslide to the water body for either subaerial or fully submerged conditions. Here we report a series of novel experiments and an analytical model that bridges this gap, by exploring the collapse of a granular column for a wide range of water depths. We show that the maximum seaward wave amplitude is governed by a single dimensionless ratio, the relative depth of submergence. Based on the experimental observations, we propose a continuous function that quantifies the maximum wave amplitude by considering the momentum flux from the initially vertical granular column to the initially still fluid. Predictions made using the momentum function are in good agreement with observations of the present study and with other experimental studies of granular column collapse at larger scales. The analytical model allows the prediction of maximum wave amplitude over the full range of submergence conditions from subaerial to partially submerged and fully submerged collapses, with potential applications for tsunami hazard assessment.
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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 | 0.000 |
| 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".