Impact of Local Scour around a Bridge Pier on Migration of Waved-Shape Accumulation of Ice Particles under an Ice Cover
Bibliographic record
Abstract
The migration of a waved-shape accumulation of ice particles under an ice cover (referred to as “ice wave” in this study) is a phenomenon of transport of ice particles during an ice accumulation process in rivers. The migration of an ice wave will affect the pier scour. On the other hand, the local scour at the pier will affect the migration of ice waves. The interaction between the migration of ice waves and local scour around a pier is a very complicated process since not only the channel bed deforms, but also the ice jam develops simultaneously. By conducting a series of flume experiments, the interaction between the local scour around bridge piers and the migration of ice waves was studied. By applying both continuity and momentum equations, an empirical equation has been derived for predicting the thickness of ice waves around the pier. The impacts of the scour hole on the thickness of ice waves around the pier have been studied. The thickness of the wave crest and the migration speed of ice waves have been investigated. Similar to a scour hole in a sand bed, an “ice scour hole” appeared at the bottom of the ice jam around the pier. The existence of the “ice scour hole” affects the development of ice waves. A formula for calculating ice transport capacity has been obtained. Results calculated using the derived formula are in good agreement with those of laboratory experiments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".