Three-dimensional levee and floodwall underseepage
Bibliographic record
Abstract
Levee and floodwall seepage models based on two-dimensional (2D) conditions can underpredict landside vertical hydraulic gradients and uplift pressures due to excavations and convex bends. The Sherman Island levee system is used to calibrate a three-dimensional (3D) seepage model to evaluate the effect of finite landside excavations and convex levee bends on landside seepage. The model shows that a 3D analysis is required for a landside excavation with an aspect ratio (length to width) less than 1L:1.5W. For drainage canals and ditches that parallel a levee or floodwall and are wider than 15 m, gradients at the excavation center are essentially equal to 2D vertical gradients but greater than 2D gradients near the excavation sidewalls. The Sherman Island calibrated seepage model also confirms concave bends diverge seepage and yield lower vertical gradients than 2D models. Varying the degree of levee curvature (ω = 45°–100°) indicates that sharper convex bends (ω = 100°; axisymmetric radius, 150 m) cause vertical gradients that can be about 150% greater than 2D analyses.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".