A model for the analysis of rapid landslide motion across three-dimensional terrain
Bibliographic record
Abstract
A new numerical model for the dynamic analysis of rapid flow slides, debris flows, and avalanches has been developed. The model is an extension of an earlier algorithm and is implemented using a numerical method adapted from smoothed particle hydrodynamics. Its features include (i) the ability to simulate flow across complex three-dimensional terrain; (ii) the ability to allow nonhydrostatic and anisotropic internal stress distributions, coupled with strain changes through frictional relationships; (iii) the ability to simulate material entrainment; (iv) a choice of different rheological kernels, including frictional, plastic, viscous, Bingham, and Voellmy; (v) a meshless solution, which eliminates problems with mesh distortion during long displacements; and (vi) highly efficient and simple operation. The model has been tested by analysing a series of laboratory flume experiments with granular materials, both on straight and curved paths. The model is capable of accurately predicting the margins of various curving flows using a single set of input parameters. A preliminary analysis of a real rock avalanche case history is also included.Key words: landslides, debris flows, rock avalanches, runout analysis, dynamic modelling, numerical methods.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".