The Impact of Flow Accelerated Corrosion (FAC) on Feeder Life Cycle Management
Bibliographic record
Abstract
Wall thinning of outlet feeder piping by flow accelerated corrosion (FAC) is a serious form of degradation affecting some CANDU® stations. The general and localized loss of wall thickness is typically highest at or near welds and changes in pipe geometry due to increased velocity or turbulence. While the process is not a high safety concern because catastrophic failure is unlikely, feeder wall thinning may result in significant economic losses as a result of forced shutdowns for repair and replacement. Accurate modelling and prediction of feeder replacements and the probability of feeder failure is not only important for continued fitness-for-service, but essential for feeder life cycle management (LCM). This paper discusses some of the key issues related to feeder FAC, and presents a probabilistic method for modelling the wall thinning process. The wall thickness loss due to FAC is modelled using a random rate model, while the probability of feeder failure is based on an empirical approach. The developed methodology allows the estimation of the remaining life of both inspected and uninspected feeder populations, while methodically accounting for the uncertainties in the problem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".