The infiltration characteristics of expansive soil subjected to drying–wetting cycles under surcharge
Bibliographic record
Abstract
This study investigates the infiltration characteristics of expansive soil subjected to drying–wetting cycles under surcharge. Infiltration tests are conducted on undisturbed expansive soil over four drying–wetting cycles. Additionally, the permeability coefficient under loading is determined prior to any drying–wetting cycles. Within the context of this study, the sample heights after drying and after wetting are monitored to determine the natural swelling and shrinkage deformations. Experimental results show that the infiltration rate decreases as the pressure increases. The sample’s swelling–shrinkage deformation decreases with each progressive drying–wetting cycle, whereas the infiltration rate consistently increases. The infiltration curve under the drying–wetting cycle can be divided into three stages according to the infiltration characteristics, which is significantly different from the infiltration curve of the sample without the drying–wetting cycle. Moreover, the proposed model can fit the infiltration curves well, and its fitting parameters are described using dimensionless pressure and the number of drying–wetting cycles. The drying of the expansive soil produces cracks that are advantageous for infiltration. Additionally, the microscopic connection between aggregates reflects changes in the internal structure of the soil during successive drying–wetting cycles. As the number of drying–wetting cycle increases, small particles aggregate into large aggregates, and the contact relationship between the aggregate changes from face–face to point–point contact, reducing the swelling potential and increasing the porosity and infiltration capacity of the soil.
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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".