ANALYSIS OF FLOW ALONG THE MEANDER PATH OF A HIGHLY SINUOUS RIGID CHANNEL
Bibliographic record
Abstract
Despite substantial research on various aspects of velocity distribution in curved meander rivers, no systematic effort has been made to analyse the variation of velocity profile along a meander path. In this research work, variation of velocity profile along the width and depth of the channel has been methodically analysed at different cross-sections (13 sections) along a meander path of a sinuous channel of 120° cross-over angle. The meander path considered is from one bend apex to the next bend apex which changes its course at the cross-over. Bend apex is the position of maximum curvature and cross-over represents the section at which the sinuous channel changes its sign. The study is thoroughly done to find the changes in the water surface profile throughout the meander path, where the height of water always remaining higher towards the outer wall of the curved channel. Longitudinal velocity distributions along the width and depth of the channel, i.e., the horizontal and vertical velocity profiles are investigated with the higher velocity remaining towards the inner wall of the channel unlike straight channels. As the channel changes its curvature, so does the movement of higher velocity which moves from one bank towards the other. Boundary shear stress distribution along different points of the wetted perimeter on the channel bed is also obtained at all the above sections to investigate its deviation along the meander path. This helped to compute the total shear force at each of these sections. Hence these features can be considered by engineers and researchers in the field of sediment erosion, deposition, etc.
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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 | 0.001 | 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".