Enhancement of Safety Analysis Capability for a CANDU-6 Reactor Using RELAP-CANDU/SCAN Coupled Code System
Bibliographic record
Abstract
The purpose of this study is the development and verification of the coupled code system SCAN and RELAP-CANDU for transient analysis of a Canada deuterium uranium (CANDU) reactor. For this purpose, a spatial kinetics calculation module is developed and implemented in SCAN, a three-dimensional (3-D) CANDU–pressurized heavy water reactor neutronics design and analysis code. Then, a dynamic linked library of the SCAN code is generated for the integration with RELAP-CANDU.The RELAP-CANDU code has been developed for best-estimate transient simulation of CANDU reactor coolant systems based on the RELAP5 code. The SCAN code is a 3-D neutronic calculation code, which is composed of both unified nodal methods based on coarse-mesh finite difference method solutions to the time-dependent two-group diffusion equations.To verify the reliability of the coupled code system RELAP-CANDU/SCAN, the 40% reactor inlet header break accident, the 100% reactor outlet header break accident, and the pump suction pipe break are analyzed. The proposed coupled thermal-hydraulic and neutronic analyses methodology shows that there is an important margin in the traditional accident analysis.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".