Simulation of hydromechanical behaviour of bentonite seals for containment of radioactive wastes
Bibliographic record
Abstract
Geological disposal of radioactive wastes relies on a multiple barrier system to provide long-term containment and isolation of the wastes. The excavation of the repository creates openings and disturbed zones in the host rock formations that need to be properly sealed. Bentonite-based materials are being considered worldwide as a preferred type of sealing material, since they possess desirable characteristics such as low permeability, high sorption capability, and swelling potential allowing them to close internal cracks and gaps at interfaces with other materials. The French Institute for Radiation Protection and Nuclear Safety (IRSN) has led an experimental program consisting of a series of laboratory and large in situ experiments to assess the hydromechanical behaviour of bentonite seals. The experiments consisted of the forced re-saturation of pre-fabricated blocks of bentonite–sand mixture, with technological voids between bentonite seals and the walls of the steel cell (in the laboratory tests) and between bentonite seals and the host rock (in the in situ experiment). Relative humidity and total stress were monitored during both tests. The Canadian Nuclear Safety Commission (CNSC) collaborated with Geofirma Engineering, IRSN, and Commissariat à l’énergie atomique (CEA) to develop a mathematical model to simulate the experiments. The model was developed within the framework of poromechanics, with the inclusion of partial saturation characteristics and swelling potential to simulate the behaviour of the bentonite-based material. The model results were in good agreement with the experimental measurements for relative humidity and swelling stresses. The model also predicted the closure of technological voids and gaps due to swelling. Although swelling into the technological voids leads to an increase in permeability, that permeability remains low and insignificant from a safety perspective.
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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".