Transient modelling of sulphide diffusion under conditions typical of a deep geological repository
Bibliographic record
Abstract
The Canadian Nuclear Waste Management Organization (NWMO) has chosen a used fuel container (UFC) design that consists of an inner steel core and outer copper coating that resists corrosion in the anaerobic underground. However, in these anaerobic conditions, microbiologically influenced corrosion (MIC) can contribute to UFC corrosion if sulphides are present in the repository. Therefore, an engineered barrier system (EBS) consisting of bentonite blocks and pellets has been designed to inhibit production of sulphide by microorganisms and impede the movement of sulphides from the host rock to the UFC. Initially, the bentonite within the deep geological repository will contain no sulphides and it will take time for sulphide from the host rock to saturate the repository. To examine the transient effect of sulphide transport and the effectiveness of the EBS, a 3D numerical model was developed capable of simulating the diffusive transport of sulphide within the NWMO repository. The model was developed using COMSOL Multiphysics, a finite element software package. The developed model included the NWMO placement room, as well as a stand-alone UFC package. Conservative assumptions such as constant-concentration boundary condition and transport-limited corrosion were assumed. The time-dependent analysis predicted the inflow of sulphide into the EBS over time, and the results showed that a steady-state condition would be reached in over 2,000 years in the placement room. The model also showed that the highest sulphide flux occurred at the semi-spherical end caps of the UFC and consequently, that corrosion from sulphide diffusion would not be uniform over the container surface.This paper is part of a supplement on the 6th International Workshop on Long-Term Prediction of Corrosion Damage in Nuclear Waste Systems.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 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".