A Dynamic Fuel Cycle Analysis for a Heterogeneous Thorium-DUPIC Recycle in CANDU Reactors
Bibliographic record
Abstract
A heterogeneous thorium fuel recycle scenario in a Canada deuterium uranium (CANDU) reactor has been analyzed by the dynamic analysis method. The thorium recycling is performed through a dry process which has a strong proliferation resistance. In the fuel cycle model, the existing nuclear power plant construction plan was considered up to 2016, while the nuclear demand growth rate from the year 2016 was assumed to be 0%. In this analysis, the spent fuel inventory as well as the amount of plutonium, minor actinides, and fission products of a multiple thorium recycling fuel cycle were estimated and compared to those of the once-through fuel cycle. The analysis results have shown that the heterogeneous thorium fuel cycle can be constructed through the dry process technology. It is also shown that the heterogeneous thorium fuel cycle can reduce the spent fuel inventory and save on the natural uranium resources when compared with the once-through cycle.
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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 | 0.001 |
| 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) | 0.000 | 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".