Physical and numerical modeling of infiltration including consideration of the pore-air phase
Bibliographic record
Abstract
Infiltration is a vadose zone process of interest to a wide range of research communities including agriculture, soil physics, and geotechnical engineering. In geotechnical engineering, transient infiltration is important to moisture balance problems such as cover systems, capillary breaks, and landslide triggering. Design of cover systems, capillary breaks, and landslide analysis applications depend on accurate models for the transient pore pressure and moisture migration response under a wide range of environmental conditions. Infiltration is typically modeled using Richards’ equation, which assumes no impedance from the pore-air phase. However, if this assumption is invalid, the ground response during infiltration is significantly affected. An optically matched pore fluid – transparent soil, which allows for high temporal and resolution measurements of degree of saturation, was used to examine the effect of air entrapment on infiltration. Homogeneous and layered profiles were subjected to closed and open infiltration conditions. Following the completion of the experimental program, the results were simulated using a finite element program that allows for consideration of the air phase during infiltration. The results show the impact of ignoring the effect of air entrapment is to significantly underpredict the time to saturation and overpredict the pore pressure response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".