The Interaction of Multi-Year Ridges with Upward Sloping Structures
Bibliographic record
Abstract
Abstract In ISO 19906 (2010), there are no algorithms provided for calculating loads on sloping structures due to interaction with multi-year (MY) ridges; only references are provided for a range of methods; to quote from Clause A.8.2.4.5.2:"Multi-year ridge actions against conical structures can be estimated using a variety of methods [Croasdale, 1980)], [Nordgren and Winker (1989)], [Wang (1984)]." A study was undertaken to revisit the theories for breaking and ride-up of MY ridges and if possible to improve them. A new simplified method for long ridges has been developed which includes secondary failures associated with the hinge pieces which are successively broken as the ridge is pushed higher prior to rotation of the broken pieces around the structure. For wide ridges, failure across their width has also been quantified and this mechanism can lower ridge loads compared to prior methods. The new method also recognizes the loads associated with the clearing of level ice fragments ahead of the ridge. The key findings have been incorporated into a methodology which is described by relatively simple equations and these are provided in the paper. Example calculations and sensitivities are provided.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".