Soil-water characteristic curve and permeability function for unsaturated cracked soil
Bibliographic record
Abstract
Cracks are widely present in natural and engineered soils. As water infiltration into a cracked soil often starts from unsaturated conditions, the soil-water characteristic curve (SWCC) and permeability function for the cracked soil are required when conducting seepage analysis. This paper presents a method to predict the SWCC and permeability function for cracked soil considering crack volume changes during drying–wetting processes. The cracked soil is viewed as an overlapping continuum of a crack network system and a soil matrix system. The pore-size distributions for the two pore systems at a particular state can be determined and used to estimate the SWCCs and permeability functions. The estimated SWCCs and permeability functions for the two pore systems can be combined to give the SWCC and the permeability function for the cracked soil at that state. Then, the SWCC and permeability function for the cracked soil at different states along a crack development path can be obtained and combined to give the SWCC or permeability function for the cracked soil considering crack volume changes. Examples are presented to illustrate the prediction of the SWCCs and permeability functions for a cracked soil along five crack development paths.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".