Benchmark Calculation of WIMS/RFSP against Physics Measurement Data of Wolsong Nuclear Power Plants
Bibliographic record
Abstract
Benchmark calculations of Canada deuterium uranium (CANDU) reactor physics design and analysis codes have been performed for a lattice code WIMS-AECL, a supercell code DRAGON, and a core analysis code RFSP by using the physics measurement data of Wolsong nuclear power plants. In this study, the lattice and reactivity device models were examined based on Wolsong-2 measurement data for the criticality and reactivity device worth. Sensitivity calculations were also performed for the number of energy groups and the cross-section library. Using the lattice and reactivity device models obtained from the Wolsong-2 calculation, the benchmark calculations were extended to the Wolsong-3 and Wolsong-4 plants. Compared to a previous study, this study showed that the results of the criticality and reactivity device worth calculations were improved when the material data were updated and the exact two-group cross sections were used. For the three nuclear power plants, the calculated core reactivity was within 0.2% Δk of criticality. The zone controller unit reactivity worth was estimated to have a maximum error of ~8%. The total reactivity worth of other reactivity control devices was consistent with the measurement data within 13%. The root-mean-square error of the flux distribution calculation was <12% when compared with flux scans performed during Phase B physics tests. In conclusion, the CANDU physics design and analysis codes used in this benchmark study predicted the physics parameters within the allowed uncertainty level of the measurement data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".