Fragmentation energy in rock avalanches
Bibliographic record
Abstract
Fragmentation is one of the mechanisms involved in rock avalanches. Quantifying the associated energy during a rock avalanche can help to assess the influence of fragmentation on post-failure mass movements. In this paper, in situ block size distributions of the intact rock mass and the debris deposits are presented and analyzed for nine rock avalanches, five in the Canadian Rocky Mountains and four in the European Alps. Degrees of fragmentation are estimated from these data. Two methods are examined to assess fragmentation energy, one based on the comminution theory, and one on the blasting energy used in the mining industry. The results show that, for the studied rock avalanches, there is a relationship between the reduction in diameter ratio, R r = D 50 /d 50 (where D 50 and d 50 are the mean diameter of the intact rock mass and the mean diameter of the debris, respectively), and the potential energy per unit volume normalized with respect to the point load strength of rock (γH G /σ c ), where γ is the unit weight of the material, H G is the vertical distance between the centres of gravity of the mass at the start and end positions, and σ c is the point load strength). For the cases studied, fragmentation energy calculations average 20% of the potential energy. An empirical relationship between R r and γH G /σ c has been established and is used in the definition of a disintegration index (I D ). This index seems to reflect the physics of the disintegration process, since it accounts for the fact that the reduction in diameter ratio is a function of the dissipated energy and the strength of the rock. These factors have long been known to affect fragmentation but have never been presented in a coherent manner for rock avalanches.Key words: rock avalanches, disintegration, fragmentation energy, Canadian Rocky Mountains, European Alps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".