Impact of (Na, Ca)NO<sub>3</sub> concentration on the deviatoric mechanical behaviour of Boom Clay
Bibliographic record
Abstract
The disposal of long-lived intermediate- and high-level radioactive waste is a major environmental concern. Deep geological disposal is widely regarded as the safest long-term solution. In Belgium, Boom Clay (BC) has been selected as the reference host formation due to its low permeability, self-sealing properties, and strong capacity to retain radionuclides. One specific waste type, Eurobitum—an intermediate-level bituminized waste—is stored in steel canisters within the repository. Over time, groundwater is expected to infiltrate the system and come into contact with these canisters. The bituminized waste swells upon water contact, releasing large amounts of (Na, Ca)NO3 and generating a saline plume that diffuses into the BC. This plume, rich in sodium ions (Na⁺), can significantly impact the clay's physicochemical and hydro-mechanical behaviour. In this study, undrained triaxial tests under isotropic consolidation were conducted on intact BC samples pre-equilibrated with (Na, Ca)NO3 solutions of varying concentrations. Solutions corresponded to sodium occupancies of 60% (1.0 mol/L) and 90% (2.0 mol/L), along with a reference Boom Clay synthetic water solution (0.015 mol/L NaHCO₃). Results showed an increase in shear strength and friction angle with sodium concentration, attributed to clay particle aggregation, shrinkage, and diffuse double layer contraction induced by salinity.
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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 | 0.000 |
| 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) | 0.001 | 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".