Overview of anaerobic corrosion of carbon steel radioactive waste packages in alkaline media in support of the Belgian supercontainer concept
Bibliographic record
Abstract
Abstract The so‐called supercontainer concept is currently being considered as the reference design for the final disposal of vitrified high‐level radioactive waste and spent fuel in Belgium. It comprises a prefabricated Portland cement‐based buffer that completely surrounds a carbon steel overpack. In this highly alkaline environment (pH ~13.6), and under normal conditions (i.e., without the ingress of aggressive species), the carbon steel overpack will be protected by a passive oxide film, which is expected to result in very low uniform corrosion rates. Considering the long timescales applicable to waste disposal, determining accurate and reliable estimates of the uniform corrosion rate under anoxic conditions forms a very important part of the safety and feasibility strategy. It is also crucial to demonstrate that no other form of corrosion apart from uniform corrosion takes place. This paper presents the progress of the research that has been made since the LTC2016 Workshop (Toronto, Canada) on uniform corrosion, pitting corrosion and stress corrosion cracking behaviour of P355 QL2 grade carbon steel exposed to an artificial concrete pore water solution.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".