Rupture Frequency of CANDU® Large-Diameter Primary Heat Transport Piping Estimated Using Probabilistic Fracture Mechanics Codes
Bibliographic record
Abstract
This paper presents a pilot study of using probabilistic fracture mechanics codes (PRO-LOCA 2009 and WinPRAISE 2007) to estimate the rupture frequency of CANDU® large diameter Primary Heat Transport (PHT) piping. The results of this study show that WinPRAISE 2007 and PRO-LOCA 2009 produce comparable trends for the predicted probability of leak and probability of large break leak. There is a number of sensitive leak detection methods available in CANDU plants. The materials and quality of fabrication and sensitive leak detection results in the total probability of a large break leak in the large diameter PHT piping welds being estimated to be on the order of 1E−8 breaks per plant per year. The results of the pilot study indicate that probabilistic fracture mechanics codes could be used to demonstrate that a shutdown action limit of 100 kg/h is sufficient to ensure the probability of rupture of large diameter PHT piping welds is extremely low.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".