Advantages of Irradiated DUPIC Fuels from the Perspective of Environmental Impact
Bibliographic record
Abstract
This study compares some properties of irradiated Direct Use of Spent Pressurized Water Reactor (PWR) Fuel In Canada Deuterium Uranium reactor (CANDU) (DUPIC) fuels with properties of other fuel cycles. The properties include the radiotoxicity, decay heat, activity, and actinide content embedded in various spent fuels or high-level wastes, which could be measures of the effectiveness of waste management. From radiotoxicity analysis of fuel cycles, the toxicity of the DUPIC option based on 1 GW(electric)·yr is much smaller than those of other fuel cycle options such as the PWR once-through mode, mixed oxide fuel recycling mode, and CANDU once-through mode. The analysis shows that the value is just about half the order of magnitude of other fuel cycles until decayed to a level below the toxicity of initial ore. This means that the DUPIC option could have an indirect benefit on the environmental effects of long-term spent-fuel disposal. From total activity analysis of various fuel cycle options, the activity per metric ton heavy metal of spent fuel is the lowest in natural uranium CANDU fuel, but in the case of activity based on 1 GW(electric)·yr, the DUPIC option has the smallest activity. In the meanwhile, from the activity analysis of 99Tc and 237Np, which are important to the long-term transport in geologic media, the DUPIC option was being contained in only about half of those other options. In conclusion, compared to other fuel cycle cases, the irradiated DUPIC fuels would have good properties from the perspective of environmental effects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".