Permeability tensor and representative elementary volume of saturated cracked soil
Bibliographic record
Abstract
Cracks are prevalent in near-ground-surface soils and provide preferential pathways for fluid flow. Cracks increase water infiltration or contaminant solute transport into soils. This paper studies the development of a permeability tensor and a representative elementary volume (REV) for saturated cracked soils. First, a method of generating random crack networks based on the statistical parameters of the crack geometry is presented. Then, the permeability tensor and REV for a crack network are studied by modeling water flow through the generated random crack networks. Finally, the permeability tensor for a cracked soil is obtained by combining the crack network and the soil matrix, and the properties of the permeability tensor and the REV for the cracked soils are investigated. Results show that the permeability tensor can be used to represent the permeability anisotropy of a cracked soil. An REV can be readily established when the crack network is relatively dense. An REV can be defined and the contribution of the crack network to permeability is small when a crack network exists in homogeneous sands. An REV is harder to establish and the hydraulic conductivity is dominated by the random crack network when a sparse crack network exists in clays.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".