Investigating the local heterogeneity of compacted bentonite/sand mixtures
Bibliographic record
Abstract
Compacted bentonite/sand mixtures have been adopted as a sealing material for the deep geological disposal of high-level radioactive wastes. However, the heterogeneity of bentonite distribution in the mixtures is inevitable, which impacts their hydro-mechanical behavior. In this study, the swelling pressure tests under constant-volume condition with various bentonite fractions and dry densities were conducted. Afterwards, local dry densities, water contents, and bentonite fractions at various positions were determined. Correspondingly, local degree of saturation was deduced from local water content and global dry density. Microstructural observation was performed by mercury intrusion porosimetry. Results showed that there was more bentonite in center and bottom zones, leading to higher dry densities and degrees of saturation. The heterogeneity was amplified at low bentonite fractions with sand skeleton formation. A critical bentonite fraction was defined as that just needed to fill the large pores inside the sand skeleton after full free swelling. If the bentonite fraction was lower than the critical value, bentonite would swell freely inside the sand skeleton with bentonite aggregate division; otherwise, the swelling of bentonite would be confined with limited aggregate structure change. These findings are helpful for understanding the formation of preferential pathways identified in gas injection tests.
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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 | 0.001 | 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".