Simulating Properties of Canadian Research Reactor Fuels Important to Disposal
Bibliographic record
Abstract
Canada has operated 17 research reactors at 11 different locations. The spent fuel from these research reactors differs significantly from CANDU fuel, which makes up the vast majority of spent fuel in Canada, and will eventually require disposal. The focus of this paper is to identify properties specific to Canadian research reactor fuel designs that would impact their suitability for disposal. The radionuclide inventory, hazardous chemical inventory, decay heat, residual enrichment, radiation decay rates, and gas generation of several Canadian research reactor fuel designs were simulated using the SCALE 6.2.4 software suite. The National Research Universal U3Si/Al dispersion rod, the National Research Experimental uranium metal X-rod, the Royal Military College UO2 SLOWPOKE-2 core, and the Whiteshell Reactor 1 uranium carbide bundle were investigated. Fuel burnup is the primary driver for the concentration of most radionuclides, hazardous chemicals, decay heat, and radiation decay rates. Carbon-14, chlorine-36, and mercury are driven by initial impurities in the fuel, which vary by fuel design. Low burnup, enriched fuels constitute a reasonable bounding case for the evaluation of criticality safety and proliferation risks. Canadian research reactor fuels are unlikely to present a greater risk of over pressurization from helium generation than CANDU fuel. Overall, the small volume of Canadian research reactor fuels requiring disposal is an important factor in the evaluation of disposal requirements.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".