Modeling the Radiolytic Corrosion of Fractured Nuclear Fuel under Permanent Disposal Conditions
Bibliographic record
Abstract
A two-dimensional model has been developed to simulate the corrosion of nuclear fuel pellets under permanent waste disposal conditions in a steel vessel with a corrosion-resistant copper shell. The primary emphasis was on the corrosion behavior within cracks with various dimensions. It was shown that a simplified α-radiolysis model which only accounts for the radiolytic production of H 2 O 2 and H 2 provides a reasonably accurate simulation and is a time-efficient alternative to the use of a model including a full α-radiolysis reaction set. Both radiolytic H 2 O 2 and H 2 can accumulate inside the cracks. However, the [H 2 O 2 ] is regulated by its reaction with UO 2 to cause corrosion and especially its decomposition to O 2 and H 2 O. This leads to [H 2 ] much greater than [H 2 O 2 ] within the cracks. The critical [H 2 ], [H 2 ] crit , required to completely suppress corrosion has been calculated for various crack widths and depths. The maximum [H 2 ] crit is only ∼ 12 times that required on a planar surface irrespective of the dimensions of the crack. The build up of H 2 within cracks is effectively a shift to more reducing conditions. As a consequence, the redox conditions within cracks begin to decouple from the external redox conditions. This makes the fuel corrosion process at these locations less sensitive than might be expected to the influences of the H 2 and Fe 2+ produced by corrosion of the steel vessel.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".