RADIONUCLIDE INVENTORY CALCULATIONS FOR DEPLETED FUEL IN A SMALL FLUORIDE MOLTEN SALT REACTOR AND A MICRO-SIZED HIGH-TEMPERATURE GAS-COOLED REACTOR
Bibliographic record
Abstract
The small modular reactor (SMR) is considered to be an enabling technology for providing economical and clean energy in remote areas in Canada. To ensure the SMR technology is developed within a robust framework that addresses environmental and waste management concerns, data are required on radionuclide inventory and characteristics of SMR depleted fuel at the end of reactor service life and at various times thereafter. These data provide essential inputs to assessment of fuel recycle analysis, understanding of environmental impact, and strategy development for waste disposal and management. In this paper, radionuclide inventories of depleted fuel in a small fluoride molten salt reactor (sm-FMSR) and a micro-sized high-temperature gas-cooled reactor (m-HTGR) are calculated using the Monte Carlo neutron transport code Serpent and the point neutron activation and decay code SCALE/ORIGEN. The inventory calculation methods for two selected small modular reactors are described, and radionuclide inventory results from Serpent and ORIGEN are compared. Overall, ORIGEN produces more conservative results than Serpent for both sm-FMSR and m-HTGR. The major characteristics of the radionuclide inventories are discussed for both SMRs.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".