Behavior of Transuranic Mixed-Oxide Fuel in a CANDU-900 Reactor
Bibliographic record
Abstract
The production of transuranic actinide fuels for use in current thermal reactors provides a useful intermediary step in closing the nuclear fuel cycle. Extraction of actinides reduces the longevity, radiation, and heat loads of spent material. The burning of transuranic (TRU) fuels in current reactors for a limited amount of cycles reduces the infrastructure demand for fast reactors and provides an effective synergy that can result in a reduction of as much as 95% of spent fuel waste while significantly reducing the fast reactor infrastructure needed. This paper examines the features of actinide mixed-oxide (MOX) fuel, TRUMOX, in a CANDU® nuclear reactor. The actinide concentrations used were based on extraction from 30-year-cooled spent fuel and mixed with natural uranium in 3.1 wt% actinide MOX fuel. Full lattice cell modeling was performed using the WIMS-AECL code, supercell calculations were analyzed in DRAGON, and full-core analysis was executed in the RFSP two-group diffusion code. A time-average full-core model was produced and analyzed for reactor coefficients, reactivity device worth, and online fueling impacts. The standard CANDU operational limits were maintained throughout operations. The TRUMOX fuel design achieved a burnup of 29.91 MWd/kg heavy element and an actinide transmutation rate of 35% for a single pass. A fully TRUMOX-fueled CANDU was shown to operate within acceptable limits and provided a viable intermediary step for burning actinides. The recycling, reprocessing, and reuse of spent fuels produces a much more sustainable and efficient nuclear fuel cycle.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".