Material Degradation in ACR-700 Fuel Channel Components
Bibliographic record
Abstract
The ACR (Advanced CANDU Reactor)-700 shares many design features with operating CANDU (CANada Deuterium Uranium) reactors, such as horizontal pressure tubes, heavy water moderator, and on-line fueling. However, there are some departures from the operating reactors that could affect the performance of structural materials. These include use of light water coolant, higher coolant pressure and temperature, enriched fuel rather than natural uranium, and higher fuel burnup. More important, the ACR-700 has many design features that set it apart from conventional and evolutionary light water reactors. This paper reviews the available literature related to design and structural materials for ACR-700 fuel channel components (Zr-2.5Nb pressure tubes, calandria tubes, annular spacers, and end fittings). The objectives were to identify the potential degradation mechanisms, evaluate the main degradation mechanism causing field failures, and analyze the available data to assess the performance of various components over the design/service life of the ACR-700. The review concludes that delayed hydride cracking (DHC) has been a primary degradation mechanism causing failure of CANDU pressure tubes. The influence of light water coolant environment on DHC initiation in the ACR 700 needs evaluation. The main concern is the potential for generation of hydrogen due to corrosion of the pressure tubes and its ingress into them, thereby making the tubes susceptible to DHC.
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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 | 0.001 | 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".