Role of Microchemistry and Microstructure on Variability in Corrosion and Deuterium Uptake of Zr-2.5Nb Pressure Tube Material
Bibliographic record
Abstract
Understanding the reasons for variability in D uptake in Canadian Deuterium Uranium (CANDU) reactor Zr-2.5Nb pressure tubes (PT)s will lead to improved surveillance and predictive strategies. Results from out-reactor aqueous exposures that suggest PT performance should be predictable based on offcut characteristics and may lead to the development of techniques to identify PTs with highest D uptake rates. The range of out-reactor corrosion and D uptake rates in Zr-2.5Nb coupons from different PT offcuts is similar to that found in test/power reactors. Out-reactor post-transition corrosion and D uptake rates at 310 and 360°C are found to be strongly correlated and decrease with increasing concentrations of Fe and Cr in the alloy. In the Bruce 3 reactor, PTs with higher D uptake show ‘curly’ α-β microstructures with a large number of basal planes (in the α-Zr grains), and β-Zr grains, oriented towards the radial direction of the tube. Since oxidized β-Zr regions are found to be associated with lateral cracking, the presence of a higher frequency of β-Zr grains aligned normal to the surface in these curly microstructures may result in increased routes for D uptake in this material. Oxide structure is also found to be dependent on the α-Zr orientation that results in different relative proportions of [001] growth versus general columnar oxide grains. Improved corrosion and D uptake performance is also found in Zr-2.5Nb material that is prefilmed (400°C for ≥24 h), β-quenched in the billet stage and in material from the back of the extrusion.
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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) | 0.001 | 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) | 0.005 | 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".