Experimental quantification of capillary and adsorbed water in active clays for hydro-mechanical modelling
Bibliographic record
Abstract
Active clays are notable for their high-swelling and sealing properties, making them valuable in various geotechnical applications, including deep repositories for nuclear waste and landfills. These properties arise from water physically adsorbed to clay particles, having an ordered structure, and greater density. Existing hydro-mechanical constitutive models for water retention behaviour prediction, which distinguish between adsorption and capillary water, are based on theoretical formulations and lack experimental validation. This work proposes a novel experimental methodology for the quantitative assessment of water adsorbed in active clays via thermogravimetric analysis. Following the proposed methodology, this work quantifies the amount of water stored (capillary and adsorbed) in active clays under controlled boundary conditions. Results show that capillary and adsorbed water are present in all hydraulic states, with the amount of adsorbed water content varying between 33% and 68% for the investigated compaction of 1.3 Mg/m 3 . Existing adsorption isotherm models are tested for the first time against experimental data for granular bentonite. The outcomes reveal the need for quantifying the amount of adsorbed water for suitably implementing microstructural models into predictive frameworks.
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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 | 0.001 |
| 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".