The Effect of pH on Nickel Alloy SCC and Corrosion Performance
Bibliographic record
Abstract
Alloy X-750 condition HTH stress corrosion crack growth rate (SCCGR) tests have been conducted at 360 C (680 F) with 50 cc/kg hydrogen as a function of coolant pH. Results indicate no appreciable influence of pH on crack growth in the pH (at 360 C) range of {approx} 6.2 to 8.7, consistent with previous alloy 600 findings. These intermediate pH results suggest that pH is not a key variable which must be accounted for when modeling pressurized water reactor (PWR) primary water SCC. In this study, however, a nearly three fold reduction in X-750 crack growth rate was observed in reduced pH environments (pH 3.8 through HCl addition and pH 4-5.3 through H{sub 2}SO{sub 4} addition). Crack growth rates did not directly correlate with corrosion film thickness. In fact, 10x thicker corrosion films were observed in the reduced pH environments.
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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".