Material Surveillance Program Regulatory Guidance for Steam Generator Tubes Extracted From Canadian CANDU Reactors
Bibliographic record
Abstract
The Canadian Nuclear Standard, CSA N285.4, requires periodic extraction of steam generator tubes for metallurgical examination; however, the Standard does not specify detailed program requirements. Therefore, Canadian Nuclear Safety Commission (CNSC) staff has recently brought forth a set of guidelines to clarify the regulatory expectations for steam generator tube material surveillance programs. This paper introduces the material surveillance program required by CSA N285.4, and provides a discussion of the CNSC staff proposed guidelines, to explain the technical basis behind the expectations for tube removal and examination. The objectives of the steam generator tube material surveillance program include evaluating inspection tool capabilities, confirming tube material performance over the life of the plant and assessing the operating environment’s potential contribution to tube degradation. The knowledge acquired from the program can reduce uncertainties associated with the non-destructive inspection practices, and can provide data for steam generator aging management programs. Over the life of a plant, CSA N285.4 requires that only a few tubes be extracted for examination. However, each tube removal is costly and represents significant personnel dose. The tube removal and examination guidelines will aid in maximizing the value of each tube extracted for metallurgical examination.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".