Physical and numerical study of lateral diversion by three-layer inclined capillary barrier covers under humid climatic conditions
Bibliographic record
Abstract
Southern China has a humid climate and often receives rainfalls that are of high intensity and (or) long duration. This paper investigates the performance of an inclined three-layer cover with capillary barrier effect (CCBE) comprising silt, sand, and gravel, for usage under humid climatic conditions. Physical modeling tests were carried out to observe the response of the three-layer CCBE system to a continuous heavy rainfall of about 70 mm/h. The layered cover model, housed in a 2 m long and 1 m wide instrumented box, is made up of 0.2 m thick silt, 0.1 m thick sand, and 0.1 m thick gravel, and the inclination of the model is 1V:3H. The movement of wetting front, changes in soil suction, and the primary components of water balance were measured during the operation of the physical models. The experimental data was used to calibrate the hydraulic parameters of the numerical model using the unsaturated flow software, SVFlux. Numerical modeling was subsequently carried out on a 60 m long inclined CCBE system to investigate the effective length of lateral diversion under prolonged rainfall. The main findings of the experimental and numerical studies are as follows: (i) the physical model tests showed that the response of the three-layer CCBE system to a heavy rainfall of 70 mm/h was different from the previous observations on experiments where the rainfall was less than 1.6 mm/h; (ii) correlation between the physical modeling and the numerical modeling indicated anisotropic behavior with respect to the hydraulic conductivity in the unsaturated sand layer; (iii) the long inclined, three-layer CCBE system (i.e., 0.6 m thick silt, 0.2 m thick sand, and 0.2 m thick gravel) had an effective length of lateral diversion over 10 m for 30 days of prolonged rainfall (i.e., 1080 mm in total).
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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 | 0.001 |
| 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".