ON HOW THE TENSILE STRENGTH OF THE SLAB AFFECTS CRACK PROPAGATION PROPENSITY
Bibliographic record
Abstract
ABSTRACT: The release of a dry-snow slab avalanche is preceded by a series of fractures. The two key processes involved are (1) failure initiation within the weak layer underlying the slab, probably due to damage accumulation by enhanced deformation, and (2) crack propagation, once the initial failure has reached a critical size – leading to the detachment of the slab. The focus on crack propagation has clearly improved our understanding of avalanche formation. The propagation saw test (PST) is the only in-situ fracture mechanical test and allows testing the crack propagation propensity. When conducting such tests, we observe that cracks sometimes only propagate a short distance, not to the end of the column, and stop at a crack through the slab. Furthermore, even if the crack propagates to the end of the column, conditions for slope failure, in other words slab avalanche release, are not always present on adjacent slopes. We calculate the tensile stress with a simple cantilever beam model and with finite element simu-lations. Results are compared to numerous PSTs from Canada to explore the relevance of slab proper-ties, in particular the tensile strength, for crack propagation. Model results suggest that the slab needs a certain density in order to have sufficient strength and not fail in tension during the initial states of crack propagation. Analyzing the field data showed that the characteristics of the slab were significantly differ-ent in those PSTs where slab fractures (SF) were observed from those where the crack propagated to the
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".