Pier scour and thin layered bed scour within a long contraction
Bibliographic record
Abstract
The paper presents an experimental investigation of (i) scour at a pier within a long contraction and (ii) scour of a thin layered bed within a long contraction. The scour depth at piers within long contractions increases with an increase in sediment size and a decrease in channel opening ratio. A theoretical calculation proposed to estimate the maximum equilibrium scour depth suggests that it is the summation of the individual equilibrium scour depth within a long contraction and the equilibrium scour depth at a pier under critical flow conditions in the upstream bed. The scour depth (relative to the approaching flow depth) within long contractions with thin gravel layers increases with an increase in the ratio of the diameter of the surface gravel to that of the bed sand and a decrease in the channel opening ratio. The scour depth within a channel contraction with a gravel layer, however, is greater than that with a unlayered bed of uniform sediment. Further, the maximum equilibrium scour depths within long contractions with gravel layers calculated theoretically using the energy and continuity equations are in agreement with the experimental data.Key words: bridge pier, contraction, scour, erosion, sediment transport, open-channel flow, hydraulic engineering.
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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 | 0.001 |
| 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".