Radiolytic Oxidation of Iodine in the Containment - Current Status
Bibliographic record
Abstract
During a hypothetical severe accident, most of the iodine entering the containment would be in particulate form that would undergo transport and deposition phenomena of aerosols. After a certain period of time, a large fraction of this aerosol would be deposited in the containment sump, either by settling or by diffusiophoresis. Dissolution of iodine compounds would result in the formation of involatile aqueous iodide ions. Under radiation, the aqueous iodide in the sump is a potential source of volatile iodine compounds.\nRadiolytic oxidation of the iodide ions in the containment sump to produce molecular iodine (I2) was considered as a major issue in the PIRT of the EURSAFE project and it is being investigated within the Source Term area (WP16) of the SARNET project. There are two major reasons for this. Firstly, I2 is a highly volatile compound, which is much more difficult to trap by physical methods than aerosols. Secondly, it can act as a precursor for organic iodide compounds, which may be even more volatile than I2.\nThis paper presents a review of the modelling fundamentals currently implemented in the main iodine chemistry codes underlying reactor accident predictions (IMPAIR3, INSPECT, IODE from ASTEC, MAAP). Some tests from the available database (AEAT tests, University of Toronto tests and others) have been simulated with those tools and the remaining uncertainties are assessed by comparison of the predictions with the data. In addition, a discussion based on a specific comparison between the two existing models in ASTEC resulted in a recommendation concerning their adequacy. Finally, short-term experimental plans to extend the database with experiments from the EPICUR programme (carried out by IRSN) are summarised.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".