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Record W2921139154 · doi:10.1201/9780429465086-115

An overview of trends and regional distribution of thermal ice loads on dams in Norway

2018· book-chapter· en· W2921139154 on OpenAlexaboutno aff
Chris Petrich, Bård Arntsen

Bibliographic record

VenueBIBSYS Brage (BIBSYS (Norway)) · 2018
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDistribution (mathematics)Physical geographyGeographyEnvironmental scienceClimatologyGeologyMathematics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.687
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.035
GPT teacher head0.265
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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