Soil-water retention and drainage during shear of an unsaturated granular material
Bibliographic record
Abstract
Loading very dense crushed sand and gravels such as in this study is well known to induce volume contraction followed by dilation. In the saturated stated, water initially outflows from the specimen during drained shearing and subsequently inflows. Unexpectedly, the same material when unsaturated expels water continuously throughout both phases of volume change. A first group of samples proves unable to maintain their saturation even under a matric suction as low as 0.14 kPa. Capillary physics elucidates how this could originate from the observed presence of a millimetre size void network (up to 6 mm). Loading of these samples produced cracking of the high air-entry porous stone. This interfered in setting the matric suction by the axis-translation technique. Modifications to moulding preparation fixed this problem and eliminated the macroporosity. Consequently, specimens proved capable of remaining saturated up to an air entry-value of 4.7 kPa. Their subsequent loading in both saturated and unsaturated states confirmed drainage observations by others. Inspecting the soil-water characteristic curve while shearing shows clear trends: water retention increases during contraction then decreases while dilating. Hence contraction acts as wetting while dilation generates drying. Examining the degree of saturation throughout shearing in function of void ratio and matric suction reveals a soil-water characteristic surface. This permits to forecast how matric suction should evolve when loading in constant water content conditions. Further testing confirms this prediction. This indicates that the water-retention characteristic surface should allow modelling other drainage conditions such as in a constant volume test. This study also concludes that loading a granular material in a dense state enables to measure its drying soil-water retention surface. Consequently, shearing a loose material should permit exploring the wetting portion of the same surface. Implications on mechanical properties are additionally investigated.
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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".