Fitness for Service Evaluation of Class 1 Piping Component
Bibliographic record
Abstract
This paper summarizes the methodology, procedure, and results of a fitness for service assessment performed for one CANDU outlet feeder in accordance with the COG FFSG Appendix E (Evaluation of Thinned Regions) ‘Level 3’. A wall thickness of 80% of the pressure-based thickness of the corresponding straight pipe is conservatively considered uniformly distributed along both tight radius bends. Plastic collapse load analyses are performed to address the pressure loading alone (E-6) and the bending moment plus coincident pressure loading (E-9). The crack initiation potential (E-10) is addressed by calculating the cumulative fatigue usage factor (Thermal & Seismic). This paper highlights the major modelling and analysis details with particular emphasis on the challenges that cut feeder models would face when dealing with the seismic load. These challenges are handled using a full length feeder model and the results from both approaches are compared. It is demonstrated that the cut feeder model for this particular feeder is more conservative compared to the corresponding full length feeder model. As such, it is expected that the full length feeder model would have a significant potential in handling the seismic issues with CANDU feeder pipes. However, more analysis work is needed to confirm and support the findings of this paper in a more general sense.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.009 | 0.001 |
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".