An overview of trends and regional distribution of thermal ice loads on dams in Norway
Bibliographic record
Abstract
Norway has over 3000 dams, over half of which are concrete dams [1]. Static ice loads are considered as part of dam design and during period safety review. They present a significant fraction of the total design load of low dams, also called small dams, common in Norway [1]. Ice loads are traditionally considered driven by the thermal expansion of ice, although measurements showed that slow water level fluctuations covering a range similar to ice thickness have the potential to cause loads of similar magnitude [2]. Commonly used static ice loads in dam design include 100 to 150 kN/m in Norway, regionally-dependent 50 to 200 kN/m in Sweden, ice thickness-dependent 150 to 220 kN/m in Canada, and at least up to 300 kN/m in Russia [3]. While the climate in Norway ranges from temperate to polar, no specific rules are in place to help select design ice loads based on regional differences. Instead, climatic conditions may be considered on a case-by-case basis. To-date, no global failures of dams due to ice loads have been reported in Norway [1], raising the question whether current design practices are too conservative.
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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 | 0.004 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".