CANDU-6 operation simulations using accident tolerant cladding candidates
Bibliographic record
Abstract
The 3D DRAGON-DONJON capabilities are exploited to simulate CANDU-6 (Canada Deuterium Uranium) core follow-up with alternate cladding materials. Aluminium-based alloys (FeCrAl and APMT), nickel-based alloys (304SS and 310SS) and silicon carbide (SiC) are compared with Zircaloy-II. High thermal captures in aluminium and nickel-based systems imply 235U enrichment, which results in a lower breeding ratio and a 1.1 ppm to a 1.4 ppm higher boron concentration than the current CANDU-6 reactor. Natural enrichment is preserved for SiC system, while providing a 3.4 mk increase in core reactivity with boron poisoning conditions similar to the reference CANDU bundle. The enriched systems’ spectral hardenings result in a 246 kW lower channel power. Throughout the cycle, the new ATF operation compliances are compared to the CANDU-6 license limits. The liquid zone controllers and adjusters effects on power flattening are investigated. An 8-bundle shift on power refueling scheme based on the CANDU channel age model is implemented and tested. The cores’ dynamic responses to a loss of regulation control event and to an instantaneous or gradual recovery of reactivity regulation devices are also studied. By uniformly perturbing the core global and bundle local parameters, new reactivity coefficients are determined and cores’ responses are compared over a large spectrum of moderate and severe accident scenarios.
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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) | 0.000 | 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) | 0.004 | 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".