Impact of armour layer on the depth of scour hole around side-by-side bridge piers under ice-covered flow condition
Bibliographic record
Abstract
Abstract In the present study, experiments were conducted in a large-scale flume to investigate the issue of local scour around side-by-side bridge piers under both ice-covered and open flow conditions. Three non-uniform sediments were used in this experimental study. Analysis of armour layer in the scour holes around bridge piers was performed to inspect the grain size distribution curves and to study the impact of armour layer on scour depth. Assessments of grain size of deposition ridges at the downstream side of bridge piers have been conducted. Based on data collected in 108 experiments, the independent variables associated with maximum scour depth were assessed. Results indicate that the densi-metric Froude number was the most influential parameter on the maximum scour depth. With the increase in grain size of the armour layer, ice cover roughness and the densimetric Froude number, the maximum scour depth around bridge piers increases correspondingly. Equations have been developed to determine the maximum scour depth around bridge piers under both open flow and ice covered conditions.
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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 | 0.001 | 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) | 0.001 | 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 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".