Main Findings, Remaining Uncertainties and Lessons Learned from the OECD/NEA BSAF Project
Bibliographic record
Abstract
The Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) Benchmark Study of the Accident at the Fukushima Daiichi Nuclear Power Station (BSAF), which started in 2012 and continued until 2018, was one of the earliest responses to the accident at Fukushima Daiichi. The project, divided into two phases, addressed the investigation of the accident at Units 1, 2, and 3 by severe accident (SA) codes until 500 h, focusing on thermal hydraulics, core relocation, molten corium concrete interaction (MCCI), and fission product release and transport. The objectives of the BSAF were to make up plausible scenarios based primarily on SA forensic analysis, support the decommissioning, and inform SA code modeling. The analysis and comparison among the institutes have brought up vital insights regarding the accident progression, identifying periods of core meltdown and relocation and reactor pressure vessel (RPV) and primary containment vessel (PCV) leakage/failure through the comparison of pressure, water level, and containment atmosphere monitoring system (CAMS) signatures. The combination of code results and inspections (muon radiography, PCV inspection) has provided a picture of the current status of the debris distribution and plant status. All units present a large relocation of core materials and all of them present ex-vessel debris with Unit 1 and Unit 3 showing evidence of undergoing MCCI. Uncertainties have been identified, in particular on the time and magnitude of events such as corium relocation in the RPV and into the cavity floor and RPV and PCV rupture events. Main uncertainties resulting from the project are the large and continuous MCCI progression predicted by basically all the SA codes and the leak pathways from the RPV to the PCV and the PCV to the reactor building and environment. The BSAF project represents a pioneering exercise that has set the basis and provided lessons learned not only for code improvement but also for the development of new related projects to investigate in detail further aspects of the Fukushima Daiichi accident.
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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 | 0.025 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".