Simulation of B9401 Test in the RD-14M Experimental Facility With CATHARE2
Bibliographic record
Abstract
RD-14M experimental facility is a full vertical-scale representation of a CANDU heat transport system, that was used as a benchmark data generating facility within the frame of IAEA’s Technical Working Group on Advanced Technologies for HWRs. RD-14M Large-Loss Of Coolant Accident (LOCA) test B9401 simulating HWR LOCA behaviour that was conducted by Atomic Energy of Canada Ltd (AECL) was selected for an international standard problem exercise. The aim was the intercomparison and validation of computer codes for thermalhydraulics safety analyses, using both codes originating within the HWR technology and also different versions of RELAP5 code, the later being developed for transient simulation of light water reactor coolant systems during postulated accidents. A report was published by IAEA in 2004. The Code for Analysis of THermalhydraulics during an Accident of Reactor and safety Evaluation (CATHARE), is also a LWR safety analysis code, developed jointly by AREVA_NP (reactors vendor), CEA (the French Atomic Energy Commission), EDF (the French electricity utility) and IRSN (the French Nuclear Safety Institute). The paper presents a model created for the RD-14M facility with CATHARE2, and the code application to the B9401 test. From the extensive series of test results available, several were selected to be compared to corresponding calculated evolutions. In some cases, our results are placed among those produced by the participants to the international standard problem with other codes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".