Validation of Water Radiolysis Models Against Experimental Data in Support of the Prediction of the Radiation-Induced Corrosion of Copper-Coated Used Fuel Containers
Bibliographic record
Abstract
Copper has been proposed as a container material for the disposal of used nuclear fuel in a number of countries worldwide. The container materials will be subject to various corrosion processes in a deep geological repository, including radiation-induced corrosion (RIC) resulting from the γ-irradiation of the near-field environment. A comprehensive model is being developed to predict the extent of RIC by coupling a radiolysis model to the interfacial electrochemical reactions on the container surface. An important component of the overall model is a radiolysis model to predict the time-dependent concentration of oxidizing and reducing radiolysis products. As a first step in the model development, various radiolysis models have been validated against experimental measurements of the concentrations of dissolved and gaseous radiolysis products. Experimental data are available for pure H2O- and Cl−-containing solutions, with and without a gas headspace. The results from these experiments have been compared with predictions from corresponding radiolysis models, including the effects of the partitioning of gaseous species (O2 and H2) at the gas–solution interface. Different reaction schemes for the Cl− radiolysis models are also compared. The validated radiolysis model will then be coupled with interfacial reactions on the copper surface and additional processes related to the presence of bentonite clay in Steps 2 and 3 of the overall model, respectively.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".