The Influence of Material Variables on Corrosion and Deuterium Uptake of Zr-2.5Nb Alloy During Irradiation
Bibliographic record
Abstract
Current CANDU2 reactors use Zr-2.5Nb pressure tubes that are extruded at 1088 K, cold-drawn 27%, and autoclaved at 673 K for 24 h. This results in a metastable, two-phase microstructure consisting of elongated α-Zr grains surrounded by a network of β-Zr filaments. To develop a mathematical model of corrosion and deuterium ingress in pressure tubes, we have considered the impact of variables including: fast neutron flux, temperature, and the asfabricated microstructure and its evolution during irradiation. Small specimens of Zr-2.5Nb are being exposed under CANDU water chemistry conditions in the Halden Boiling Water Reactor.3 The experiments involve fast neutron fluxes (E ≥ 1.05 MeV) of 0, 1.7, and 4.5 × 1017 n ∙ m-2 ∙ s-1, and temperatures of 523 and 598 K. Specimens have been prepared from pressure tube materials representative of all current CANDU reactors, materials subject to thermal decomposition of the β-Zr phase, and tubes extruded over a range of conditions. Results from the first three years of the Halden test program are summarized. At both 523 and 598 K, tubes made of β-quenched material exhibit lower oxidation rates than those made from non-β-quenched materials. In short-term out-of-flux exposures at 523 K, three non-β quenched tubes appear to show linear oxidation kinetics. Similar behavior is not observed in tests conducted out-of-flux at 598 K, or in-flux at either temperature. At 598 K, β-quenched tubes exhibit significantly lower deuterium pickup rates than non-β-quenched tubes. When tested at 598 K, thermally aged specimens show declining oxidation and deuterium pickup rates with increasing β-Zr phase decomposition. At 523 K, the impact of thermal aging was less significant. Preliminary results from an “extrusion variable test” suggest that tubes fabricated according to the current CANDU specification show the best corrosion resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".