Numerical Modelling of Permafrost Degradation Effects on Rock Slopes
Bibliographic record
Abstract
Rockfalls and rockslides are being observed with increased frequency in high mountains during last decades. Permafrost degradation, driven by global warming, is considered to be the main triggering factor. This paper describes a series of Distinct Element simulations of a selected rock face, where the presence of ice in joints is taken into consideration. These simulations are part of a wider multi-scale approach to modelling of potentially rock slopes. Previous research at the material scale (ice and frozen soil) allowed defining an original failure criterion for continuous and discontinuous rock joints filled with ice. This criterion is now included in large scale DEM model of punta Gnifetti (4554 m asl - Monte Rosa massif) in order to reproducing the actual configuration through back-analysis based on geomechanical investigation, and assessing evolutionary scenarios driven by the increase of persistence and of temperature. Relevant numerical issues, regarding boundary conditions and model generation are preliminary discussed, as well.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".