Experimental Assessment of Scour Around Side-by-Side Double Piers in an S-Shaped Channel with Ice-Jammed Flow
Bibliographic record
Abstract
Through laboratory experiments in an S-shaped channel, this study analyzes how the flow Froude number, the ratio of ice-to-flow rate, pier spacing-diameter ratio, and bed material median grain size influence scour depth around side-by-side double piers under ice-jammed flow conditions. Unlike the development of a scour hole around a bridge pier in a straight channel, where the scour depth increases with the flow Froude number under ice-covered conditions, this study reveals that in an S-shaped channel, scour depth increases with the flow Froude number near the convex bank pier and decreases near the concave bank counterpart. Irrespective of ice conditions, a higher ratio of pier spacing-diameter correlates with augmented scour depth at the convex bank and diminished scour at the concave bank. As the ice-to-flow rate ratio increases, the ice jam thickness in the S-shaped channel also increases, leading to a significant decrease in the flow area and resulting in deeper scour holes around the piers. Equations have been developed to calculate the maximum scour depth around side-by-side double piers positioned in an S-shaped channel with ice-jammed flow.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".