Influence of Alloying Elements and Chloride Concentration on the Galvanic Corrosion of Ferrous Alloys Coupled to Graphite for SMR Waste Applications
Bibliographic record
Abstract
Abstract As the deployment of small modular nuclear reactors (SMR) in Canada approaches, waste management considerations become increasingly critical. This study investigates the potential degradation mechanisms during the initial dry storage phase of TRISO fuel waste storage containers. Specifically, this research explores the possible galvanic corrosion of the graphite outer casing of TRi-structural ISOtropic (TRISO) fuel and the carbon steel storage material, resulting from the ingress of air/water. Proximity to water sources can exacerbate corrosion, particularly due to the presence of Cl ions. Additionally, water radiolysis may lead to the formation of hydrogen peroxide and nitric acid, further influencing corrosion rates. This study examines the galvanic coupling between graphite and ferrous alloys under varying concentrations of NaCl to identify concentrations that may significantly impact material integrity. Electrochemical testing along with immersion testing were employed to determine the extent of galvanic coupling at varying NaCl concentrations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".