Channel Bed Deformation and Ice Jam Evolution around Bridge Piers
Bibliographic record
Abstract
The interaction between the evolution of an ice jam and the local scour at bridge piers becomes much more complicated due to the evolution of both the channel bed and ice jam. Thus, research work regarding this topic has been hardly conducted. In the present study, experiments under different flow conditions with three different pier shapes were carried out. Through laboratory experiments, the development of scour holes around bridge piers under open flow, ice-covered, and ice-jammed flow conditions was compared. The results show that under the same hydraulic condition and with the same ice discharge rate (Qi/Q), the development of an initial ice jam with a local scour around bridge piers along the entire flume takes a relatively short time. However, it takes a longer time for an ice jam to achieve an equilibrium state. With the presence of a local scour at bridge piers, after an ice jam reaches an equilibrium state, the ice jam thickness, water level, and water depth for flow are relatively larger compared to that without a local scour at the pier. The equilibrium ice jam thickness around the pier is negatively correlated with the initial flow Froude number. When the development of an initial ice jam is dominated by a mechanical thickening process, the rate of the development of a scour hole around a pier is faster. On the other hand, when the development of an initial ice jam is dominated by a hydraulic thickening process, the development of a scour hole around a pier can be treated as a scour process under an ice-covered flow condition. An equation was developed to determine the scour depth around a pier under an ice-jammed flow condition by considering related factors such as the flow Froude number, ice jam thickness, and ice discharge rate. The results of this research can provide a reference for bridge design and safety protection, as well as the interaction mechanism of local scour and ice jam evolution.
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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 | 0.000 |
| 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 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".