The Development and Use of T2GGM: A Gas Modelling Code for the Postclosure Safety Assessment of OPG’s Proposed L&ILW Deep Geologic Repository, Canada
Bibliographic record
Abstract
As part of the postclosure safety assessment of Ontario Power Generation’s (OPG’s) proposed Deep Geologic Repository (DGR) for Low and Intermediate Level Waste (L&ILW) at the Bruce site, Ontario, a Gas Generation Model (GGM) has been developed and used to model the detailed generation of gas within the DGR due to corrosion and microbial degradation of the organics and metals present. The GGM is based on a kinetic description of the various microbial and corrosion processes that lead to the generation and consumption of various gases. It takes into account the mass-balance equations for each of the species included in the model, including three forms of organic waste (cellulose, ionexchange resins, and plastics and rubbers), four metallic waste forms and container materials (carbon and galvanised steel, passivated carbon steel, stainless steel and nickel-based alloys, and zirconium alloys), six gases (CO2, N2, O2, H2, H2S, and CH4), five terminal electron acceptors (O2, NO3−, Fe(III), SO42−, and CO2), five forms of biomass (aerobes, denitrifiers, iron reducers, sulphate reducers, and methanogens), four types of corrosion product (FeOOH, FeCO3, Fe3O4, and FeS), and water. The code includes the possibility of the limitation of both microbial and corrosion reactions by the availability of water. The GGM has been coupled with TOUGH2 to produce T2GGM; a code that models the generation of gas in the repository and its subsequent transport through the geosphere. T2GGM estimates the peak repository pressure, long time repository saturation and the total flux of gases from the geosphere. The present paper describes the development of T2GGM and the numerical modelling work undertaken to calculate the generation and build-up of gas in the repository, the two-phase exchange of gas and groundwater between the repository and the surrounding rock, and between the rock and the surface environment. The results have been used to inform the safety assessment modelling.
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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 | 0.000 | 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".