THE EFFECTS OF TYPICAL THORIUM IMPURITIES ON THORIUM-BASED NUCLEAR FUELS
Bibliographic record
Abstract
Natural thorium contains impurities of numerous isotopes. A study was performed to examine the influence of naturally occurring impurities in thorium-based fuels on a few parameters of interest such as: exit burnup, coolant void reactivity (CVR), fuel temperature coefficients (FTC), and the radiotoxicity of the used fuel. Two different fuel bundle designs were modeled: a 43-element bundle containing 2.25% U-233, and a 35-element bundle containing 1.45% U-233. Naturally occurring thorium fuel impurities were applied to both fuel bundle models at various concentrations, from 0% to 100% of the expected maximum. For burnup-averaged k-infinity (k∞) values of 1.050 and 1.030, exit burnup, burnup-weighted CVR, and burnup-weighted FTC were calculated using the neutron transport code WIMS-AECL, and plotted against fraction of full impurity concentration to determine how the impurity levels affect these reactor physics parameters of interest. For the most-realistic (for CANDU) burnup-averaged k∞ of 1.050, both the inhalation radiotoxicity and the production of U-232 were calculated using the fuel depletion code WOBI. Up to the maximum impurity concentrations considered, no effects on the investigated fuel performance parameters were found to be greater than a few percent.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".