Evaluation of Flow Accelerated Corrosion of PWR Secondary Piping by Coupling Analysis of Corrosion and Flow Dynamics
Bibliographic record
Abstract
Abstract Systematic approaches for evaluating flow accelerated corrosion (FAC) are desired before discussing application of countermeasures for FAC. Firstly, future FAC occurrence should be evaluated to identify locations where a higher possibility of FAC occurrence exists, and then, wall thinning rate at the identified FAC occurrence zone is evaluated to obtain the preparation time for applying countermeasures. Wall thinning rates were calculated with the coupled models of static electrochemical analysis and dynamic double oxide layer analysis. Anodic current density and electrochemical corrosion potential (ECP) were calculated with the static electrochemistry model based on an Evans diagram and ferrous ion release rate determined by the anodic current density was applied as input for the dynamic double oxide layer model. Some of the dissolved ferrous ion was removed to the bulk water and others precipitated on the surface as magnetite particles. The thickness of oxide layer was calculated with the dynamic double oxide layer model and then was applied as input for the electrochemistry model. It was confirmed that the calculated results of the coupled models resulted good agreement with the measured ones.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".