The Effect of Minor Alloying Elements on Oxidation and Hydrogen Pickup in Zr-2.5Nb
Bibliographic record
Abstract
In CANDU® reactors, fuel and coolant are contained in horizontal pressure tubes made of Zr-2.5 wt% Nb alloy. In the past decade, the effect of more than 20 impurity elements, in various concentrations, on oxidation and deuterium pickup (at 300°C, pD = 10.5, Li2O) have been investigated in over 70 Zr-2.5Nb alloys. The studies were performed using non-consumable arc-melted alloy logs that were rolled and made into corrosion coupons and corroded in autoclaves. This study represents one of the largest collections of previously unpublished data on the effect of impurity elements on oxide film growth and deuterium pickup in a zirconium alloy. Elements such as Al, Ti, Mn, and Pt, to name but a few, were found to significantly accelerate the corrosion process. Some elements, such as tin, had a positive effect on oxidation (lowers the rate of oxide film development) and a negative effect on hydrogen pickup (increases pickup). Three parameters were important to the corrosion process, namely, microstructure, surface finish, and synergistic interactions between the impurity elements. The above studies culminated in two response surface analyses (RSA). The first was conducted on the effect of C and Fe on oxygen and deuterium pickup in Zr-2.5Nb drop castings corroded at 325°C in CANDU® conditions. The second study was performed in autoclaves at 300°C on the affect of four impurity elements, C, Fe, Cr, and Si, in Zr-2.5Nb micro-tubes, which possess the same microstructure as full-size pressure tubes. The first RSA revealed a quadratic dependence of corrosion on C and Fe concentrations, with an optimum resistance at about 30 ppm (wt) C and 1100 ppm (wt) Fe. This has been partially confirmed by out-reactor corrosion of Zr-2.5Nb-Fe micro-pressure tubes. Trends in-and out-reactor were similar for oxidation but different in magnitude for deuterium pickup. There is no linear dependence on the Fe concentration in-reactor, implying that Fe and C form a complex. The second RSA showed no effect due to Si. Cr weakly influenced oxide film formation, at least for short-term exposures.
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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 | 0.000 |
| 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) | 0.001 | 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".