ASTEC, COCOSYS, and LIRIC Interpretation of the Iodine Behaviour in the Large-Scale THAI Test Iod-9
Bibliographic record
Abstract
The large-scale iodine test Iod-9 of the German THAI programme was jointly interpreted by means of post-test analyses within the THAI Circle of the SARNET/WP16. In this test, molecular iodine (I2) was injected into the vessel dome of the 60 m3 THAI vessel to observe the evolution of its distribution between water, gas, and surfaces. The main processes addressed in Iod-9 are (a) mass transfer of I2 between the gas and the two sumps, (b) iodine transport in the main sump when it is stratified and then mixed, and (c) I2 adsorption onto, and desorption from, the vessel walls in the presence and absence of wall condensation. The codes applied by the THAI Circle partners were ASTEC-IODE (IRSN), COCOSYS-AIM (GRS) and LIRIC (AECL). IODE and AIM are semi-empirical iodine models integrated in the lumped-parameter codes ASTEC and COCOSYS respectively. With both codes multi-compartment iodine calculations can be performed. LIRIC is a mechanistic iodine model for single stand-alone calculations. The simulation results are compared with each other and with the experimental measurements. Special issues that were encountered during this work were studied in more detail: I2 diffusion in the sump water, I2 reaction with the steel of the vessel wall in gaseous and aqueous phases, and I2 mass transfer from the gas to the sump. Iodine transport and behaviour in THAI test Iod-9 are fairly well simulated by ASTEC-IODE, COCOSYS-AIM and LIRIC in post-test calculations. The measured iodine behaviour is well understood and all measured data are found to be consistent. The very slow iodine transport within the stratified main sump was simulated with COCOSYS only, in a qualitative way. Consequently, this work highlighted the need to improve modelling of (a) the wet iodine adsorption and the washdown from the walls, (b) the I2 mass transfer between gas and sump, and (c) the I2/steel reaction in the gaseous and aqueous phases. In any case, the analysis of the large-scale iodine test Iod-9 has been an important validation step for the codes applied.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".