Main outcomes of OECD/NEA THAI-2 project on hydrogen risk and source term investigations: Data application for code validation and containment safety assessment
Bibliographic record
Abstract
During a core-melt accident, apart from hydrogen, radioactive gases and aerosols are released into the containment, the behaviour of which is of significant importance for determining the radiological source term. The investigation of in-containment combustible gases and fission product behaviour was the subject of the OECD/NEA THAI-2 project conducted during 2011–2014. The project focused on experiments on hydrogen behaviour i.e., deflagration in the presence of spray and passive autocatalytic recombiners (PARs) performance in O 2 -lean atmosphere, on the interaction of molecular iodine with reactive (silver) and non-reactive (tin oxide) aerosol particles to assess the effect on a potential source term, and on the quantification of the release of gaseous iodine from a flashing jet, representing a PWR steam generator tube rupture scenario during reactor shutdown. The project was supported by 11 countries involving safety organizations, regulatory bodies, research laboratories, universities and industries. The experimental programme of the OECD/NEA THAI-2 project strongly contributed to the validation and further development of advanced lumped parameter and computational fluid dynamic codes used for reactor applications by e. g. providing experimental data for code benchmark exercises. The present paper summarizes the key findings of the project and highlights the importance of project results for mitigation of hydrogen risk and source term related issues. Furthermore, the use of project results by the project partners for code validation and reactor analyses towards management and mitigation of a severe accident in light water reactors is discussed with selected examples.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".