Overview and outcomes of the OECD/NEA benchmark study of the accident at the Fukushima Daiichi NPS (BSAF) phase II – results of severe accident analyses for unit 2
Bibliographic record
Abstract
The Phase 2 of the OECD/NEA project "Benchmark Study of the Accident at the Fukushima Daiichi Nuclear Power Plant (BSAF)" was established in mid-2015. The objectives have been similar to phase 1 of the project but with an extended analysis period of 3 weeks from the occurrence of the earthquake, a major focus on fission product (FP) behavior and releases to the environment, and the comparison to various data including radiological data and results of backwards calculations of the source term. Nine organizations of six countries (CNL Canada; CRIEPI, IAE, JAEA and NRA Japan; IRSN France; KAERI Korea; NRC/DOE/SNL U.S.A. and VTT Finland) submitted results of their calculated severe accident scenarios for Unit 2 of Fukushima Daiichi using different severe accident codes (ASTEC, MAAP, MELCOR, SAMPSON, THALES-KICHE). The present paper describes the findings of the comparison of the participants' results for Unit 2 against each other and against plant data, the evaluation of the accident progression and the final status inside the reactors. Special focus is on RPV status, melt release and FP behavior and release. Unit 2 specific aspects will be highlighted and points of consensus as well as remaining uncertainties and data needs will be summarized. The results for Units 1 and 3, and an overall summary are presented in separated papers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".