Écoulement saturé et non saturé de l’eau souterraine vers des drains en aquifère à nappe libre
Bibliographic record
Abstract
The drainage of sports fields, highways, farm lands, and covers for wastes corresponds to the drainage of a shallow unconfined aquifer resting on a horizontal or sloping impervious substratum. The seepage, partly saturated and partly unsaturated, is thus described by nonlinear equations that are not easy to solve. A few analytical solutions exist; they were obtained after several simplifying assumptions. Are they realistic? In this paper, comparisons are made between predictions from analytical solutions and those from numerical resolutions (for saturated and unsaturated seepage) under steady and transient states. The analytical solutions predict a water table and flow rates that differ significantly from those of the numerical resolutions, and are sometimes unrealistic. Corrections to the analytical solutions have already been proposed to account for the vadose zone. Despite such corrections, the published solutions to drainage problems may be inaccurate. In engineering projects where the duration of drainage may be critical for the construction schedule, it is recommended to avoid the analytical equations and to use numerical codes that solve the complete differential equations by taking into account the complete soil characteristic curves for hydraulic conductivity and capillary retention, which can be obtained using permeability tests and capillary-retention tests.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.007 | 0.001 |
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".