Quantitative analysis of RD-14M large LOCA test B9401 calculations
Bibliographic record
Abstract
The results obtained in a more-than-a-decade application of thermal-hydraulic system codes to the analysis of experiments performed in Integral Test Facilities (ITF) and Separate Effect test Facilities (SETF) including the participation to several International Standard Problems (ISP) and Standard Problem Exercises (SPE), organized by OECD/NEA/CSNI (Organization for Economic Cooperation and Development / Nuclear Energy Agency / Committee on the Safety of Nuclear Installations) and by IAEA (international Atomic Energy Agency), respectively, suggested the need for new methods and procedures for code application. The words nodalization-qualification, qualitative-accuracy-evaluation, quantitative-accuracy-evaluation, and acceptability-thresholds were introduced. \n \nThe present document deals with accuracy quantification at the transient level in relation to the Large Break Loss of Coolant Accident (LB-LOCA) test B9401 performed in RD-14M facility availbale at the Manitoba Research center of AECL in Canada. The FFTBM (Fast Fourier Transform Based method) developed at UNIPI was applied and a hierarchy of calculation quality by various participants was determined.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".