Laboratory characterization and discrete element modeling of shrinkage and cracking in clay layer
Bibliographic record
Abstract
The performance of a variety of geostructures, such as compacted clay liners, earth dams, and pavement embankments, is compromised by soil cracking. Experiments are set up to monitor the drying process of a clay layer under controlled temperature and humidity conditions. The gravimetric water content and images are captured automatically. Volumetric shrinkage of the bentonite sample as well as the crack patterns are determined from images. The monitored volumetric strain development is used to implement the discrete element method (DEM) to simulate the drying shrinkage and desiccation cracking. Model parameters are calibrated through unconfined compression tests on clay specimens at different water contents. This simplified calibration procedure allows characterization of the soil behaviors in the mesoscale and bypass the complex physicochemical processes involved. The initiation and propagation of cracks from the DEM model agree well with the phenomena observed in the laboratory experiments. The influence of boundary constraint and sample thickness on the crack patterns is analyzed, which includes the use of hydrophobic coating to diminish the boundary constraint. Major features of desiccation cracking can be replicated with the computational procedures. Boundary constraint, including surface roughness and strength of boundary layer, is found to significantly influence the final crack patterns.
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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".