Key Parameters to Determine Wall Thinning Due to Flow Accelerated Corrosion
Bibliographic record
Abstract
In order to predict occurrence of flow accelerated corrosion (FAC) and to estimate wall thinning rate due to FAC, six step calculation procedures have been proposed. In the procedures, FAC is determined by six parameters, i.e., the flow dynamics parameter, chromium content in materials, temperature, pH, oxygen concentration, and ferrous ion concentration ([Fe2+]) in bulk water. The high FAC risk zones were evaluated by the maximum wall thinning rates, which were determined by a function of 1D FAC parameters. At the indicated high FAC risk zone, 3D distributions of mass transfer coefficients were obtained and then wall thinning rates were calculated with the coupled model of static electrochemical analysis and dynamic oxide layer growth analysis. In the paper, the effects of all parameters except that related to [Fe2+] on FAC occurrence have been discussed and then the effects of [Fe2+] on wall thinning are discussed.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".