Recycling option search for a 600-MWe sodium-cooled transmutation fast reactor
Bibliographic record
Abstract
Four recycling scenarios involving pyroprocessing of spent fuel (SF) have been investigated for a 600-MWe transmutation sodium-cooled fast reactor (SFR), KALIMER. Performance evaluation was done with code system REBUS connected with TRANSX and TWODANT. Scenario Number 1 is the pyroprocessing of Canada deuterium uranium (CANDU) SF. Because the recycling of CANDU SF does not have any safety problems, the CANDU-Pyro-SFR system will be possible if the pyroprocessing capacity is large enough. Scenario Number 2 is a feasibility test of feed SF from a pressurized water reactor PWR. The sensitivity of cooling time before prior to pyro-processing was studied. As the cooling time increases, excess reactivity at the beginning of the equilibrium cycle (BOEC) decreases, thereby creating advantageous reactivity control and improving the transmutation performance of minor actinides. Scenario Number 3 is a case study for various levels of recovery factors of transuranic isotopes (TRUs). If long-lived fission products can be separated during pyroprocessing, the waste that is not recovered is classified as low- and intermediate-level waste, and it is sufficient to be disposed of in an underground site due to very low-heat-generation rate when the waste cooling time becomes >300 years at a TRU recovery factor of 99.9%. Scenario Number 4 is a case study for the recovery factor of rare earth (RE) isotopes. The RE isotope recovery factor should be lowered to ≤20% in order to make sodium void reactivity less than <7$, which is the design limit of a metal fuel.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".