Swelling pressures and hydration times in a clay seal
Bibliographic record
Abstract
Underground repositories for nuclear fuel waste will eventually become filled, and access shafts will have to be sealed. In many international studies, the preferred sealant is a compacted sand–bentonite mixture in which montmorillonite in the bentonite swells as it absorbs groundwater and develops swelling pressure. Lowered porosities in the bentonite lead to reduced hydraulic conductivity. Sealing is most effective when the seal is saturated and swelling pressure has been maximised. The time required to reach complete hydration is important. This paper describes the development of swelling pressures during hydration of a field-scale shaft-sealing experiment at Canada’s underground research laboratory. Numerical modelling used the finite-element program Code_Bright and hydro-mechanical parameters from laboratory tests to determine time-dependent porosities, total pressures and degrees of saturation in the full-scale field project. Data from laboratory-scale ‘wetting’ tests on specimens of seal material were then used in models by Liu and Dueck and Börgesson to evaluate changes in swelling pressures with time. Six years of data from field instruments indicate that the seal was functioning as designed. In the future, when the seal becomes fully hydrated and reaches stress equilibrium, the modelling suggests that swelling pressures in the seal will be in the range of 0.43–0.86 MPa. This is broadly similar to the value of 0.8 MPa suggested by a separate series of laboratory swelling tests. Full saturation and maximum swelling pressure can be expected in 17–19 years after the seal has been completed.
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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 | 0.000 | 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".