Benchmarking MCNP and WIMS/RFSP against Measurement Data—I: Deuterium Critical Assembly
Bibliographic record
Abstract
Benchmark calculations have been performed for the conventional Canadian deuterium uranium (CANDU) core analysis code RFSP and the Monte Carlo code MCNP-4B using experimental data from the deuterium critical assembly. The benchmark calculation was carried out for the effective multiplication factor (keff), void reactivity, local power peaking factor (LPPF), and power distribution of a uniform core with 1.2 wt% UO2 and two-region cores with PuO2-UO2 fuels. The RFSP calculation was performed with two energy groups, using lattice parameters generated by WIMS-AECL with the ENDF/B-V cross-section library. The RFSP calculation has shown that the root-mean-square (rms) errors of the keff and the void reactivity are within 0.6% δk and 0.3% δ(1/k), respectively. The MCNP simulation was performed using a fully heterogeneous core model that explicitly describes the individual fuel rod and channel. The simulation showed an excellent agreement for the keff against the measurement, while the rms error of the void reactivity was 0.4% δ(1/k). The LPPF and core power distribution estimated by both codes matched those of the measurements within 4 and 9%, respectively. Conclusively, the physics analysis by the RFSP code in conjunction with the WIMS-AECL produces credible results for the light water–cooled and heavy water–moderated system. In addition, the MCNP-4B code has proved its potential as a computational benchmarking tool for the heavy water–moderated system.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".