Assessment of Adequacy of Upper-Shelf Fracture Toughness Model for Zr-2.5Nb Pressure Tubes for Fitness-For-Service Evaluations
Bibliographic record
Abstract
Abstract The fracture toughness of Zr-2.5%Nb pressure tubes in CANDU®1 reactors is an important material property for evaluation of protection against fracture and demonstration of leak-before-break. A probabilistic predictive model for fracture toughness of irradiated pressure tubes in the upper-shelf temperature regime was developed on the basis of material surveillance results. The model was subsequently incorporated into the Canadian Standards Association (CSA) Standard N285.8 as the reference model in fitness-for-service evaluations of pressure tubes that use the upper-shelf fracture toughness as an input. As required by CSA Standard N285.4, the model is to be periodically reviewed with material surveillance results of upper-shelf fracture toughness to evaluate its adequacy as a representative model. New burst-test data for upper-shelf fracture toughness have been obtained from ex-service surveillance pressure tubes and other experimental programs since the upper-shelf fracture toughness model was developed. Assessment of the adequacy of the upper-shelf fracture toughness model for Zr-2.5%Nb pressure tubes for continued use in fitness-for-service evaluations was performed, as documented in this paper.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".