An efficient multi-layer model for pier scour computations
Bibliographic record
Abstract
Pier scour has caused bridge failures with catastrophic consequences. The aim of this study was to develop and verify a mathematical model for pier scour predictions. A new approach is taken that combines shallow-water equations with non-hydrostatic pressure corrections and a non-uniform mesh in the horizontal with terrain-following layers in the vertical. This approach significantly improves computational efficiency from the conventional computational fluid dynamics approach. It is concluded that, emerging from the lateral sides of a pier (cylinder), scour deepens while the patterns migrate upstream towards the pier's upstream nose. On the upstream side, scour continues to grow until the bed slope reaches the angle of repose of sediments. On the downstream side, scour grows until equilibrium is reached. The scour hole is shallower downstream than upstream of the pier. The presence of the pier causes a strong downflow near its upstream nose, a strong vortex at its foot on the upstream side and a weak vortex on the downstream side. The predicted flow velocity and scour depth agree well with measurements. The terrain-following layer feature is particularly useful for scour computations; the high efficiency makes the model practical for field-scale applications, which are highly relevant to improved design of pier foundations and pier scour control.
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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 | 0.000 |
| 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".