Bibliographic record
Abstract
Diversion canals supplemented with upstream and downstream cofferdams are constructed to divert river flow for the construction of diversion weirs. Insufficient canal capacity leads to overtopping of water from the crest of the upstream cofferdam and sides of the diversion canal, which is regarded as the dominant risk mode in the system. A dynamic reliability model, which is based on a resistance-loading methodology with random independent loading following a Poisson process and random fixed resistance, may be used to assess the risk levels for various return periods and construction duration of a diversion weir. The system resistance is considered as the maximum canal capacity described by a lognormal probability density function. The river flow rate corresponding to a certain return period is considered as the external loading on the system. In a case study, a dynamic reliability analysis is performed for a diversion facility. From a flood flow frequency analysis, log-Pearson type 3 distribution is selected to describe the loading. The relationships between the total cost of the diversion facility, its reliability, safety, and duration of construction are examined in a decision making framework.Key words: dynamic reliability, diversion facility, resistance, loading.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".