Large-scale brittle and ductile toppling of rock slopes
Bibliographic record
Abstract
Slow, ductile toppling of rock masses commonly creates large-scale mountain slope deformations. In some cases, rock toppling can initiate an extremely rapid catastrophic landslide. This theoretical and field-based study was aimed at distinguishing the two alternative modes of toppling. The idea that certain key parameters of the undeformed rock mass may influence failure behaviour in a quantifiable way was examined through a parametric study of a large rock slope using the universal distinct element code (UDEC). The slope was modelled using variations of rock mass strength, discontinuity orientation and persistence, and toe over-steepening. The results indicated two distinct types of failure behaviour: (i) ductile, self-stabilizing flexural toppling in weak rock with a single dominant joint set; and (ii) brittle, catastrophic block toppling in strong rock containing persistent, down-slope oriented or horizontal cross-joints, which act as surfaces of separation at the base of the toppling blocks. The two mechanisms exhibit very different patterns of prefailure stress. During flexural toppling, the major principal stress is oriented predominantly parallel with the slope surface. In the case of block toppling, it is vertical and a large part of the unstable volume is horizontally destressed. Boundaries between the two types of behaviour have been approximately mapped. Two field case studies were then examined in light of the results. The first case involves a block topple in strong granitic rocks that failed catastrophically and produced a high velocity rock avalanche; and the second case is a large flexural topple in metamorphic rocks, exhibiting slow deformations.Key words: rock toppling, landslide, distinct element model, parametric study, 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 | 0.001 |
| 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 | 0.000 | 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".