Numerical Modeling of Water Flow in Permeable Friction Course Pavement During Rainfall Considering Rainfall Intensity and Suction Pressure
Bibliographic record
Abstract
This study developed a numerical model to observe the water flow in permeable friction course pavement (PFCP) during rainfall events. The model was established based on FeniCS, which is widely known as an open-source computing platform for solving partial differential equations. The results showed that rainfall intensity significantly affected time for surface ponding in the PFCP. A higher rainfall intensity resulted in a lower time for surface ponding of the PFCP. The evaluation for the effect of suction pressure on the PFCP showed that the suction pressure in the PFCP had a remarkable effect on the time for surface ponding. As the suction pressure in the PFCP increased, the time for surface ponding increased. The results in this study are based on numerical modeling. In the future, further experimental studies in the laboratory and in the field are needed to validate the water flow in PFCP during rainfall events considering other factors such as permeability, rutting, and environmental factors.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".