A method to predict desiccation crack depth in a compacted clayey soil
Bibliographic record
Abstract
Estimation of crack depths and spacing due to desiccation of clayey soils is needed to predict changes in mechanical or hydraulic properties in the cracked layer. These changes affect the infiltration of water, stability, and deformation of a soil mass. Desiccation cracks are associated with increasing suction due to moisture loss accompanied by restrained shrinkage, which results in tensile stresses in near surface soil layers. Cracks propagate when the developed tensile stresses exceed the tensile strength of soil. A simple analytical method is presented to predict crack depths in compacted clayey soil due to changes in matric suction with depth. The model equation is based on the Hookean elastic equation relating incremental strain to incremental stress and incorporates two stress state variables including net normal stress and matric suction. Input to the model equation includes the tensile strength and elastic parameters, and to complete the prediction of crack depth, the suction change profile of interest is needed. The method validity was investigated by comparing predicted crack depths to those observed in soil compacted in a bench scale apparatus for studying desiccation cracking. Tensile strength and elastic properties were determined from tests conducted on soil during desiccation under approximate uniaxial conditions. Predicted crack depths were obtained based on changes in suction interpreted from water content sensors at various depths in the soil bed and compared favorably to observed desiccation crack depths.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".