Numerical and Experimental Study of Dividing Open-Channel Flows
Bibliographic record
Abstract
Dividing flows in open channels are commonly encountered in hydraulic engineering systems. They are inherently three-dimensional (3D) in character. Past experimental studies were mostly limited to the collection of test data on the assumption that the flow was 1D or 2D. In the present experimental study, the flow is treated as 3D and test results are obtained for the flow characteristics of dividing flows in a 90° , sharp-edged, rectangular open-channel junction formed by channels of equal width. Depth measurements are made using point gauges, while velocity measurements are obtained using a Dantec laser Doppler anemometer over grids defined throughout the junction region. A 3D turbulence model is also developed to investigate the dividing open-channel flow characteristics. The predicted flow characteristics are validated using experimental data. Following proper model validation, the numerical model developed can yield design data pertaining to flow characteristics for different discharge and area ratios for other dividing flow configurations encountered in engineering practice. Energy and momentum coefficients based on the present 3D model yield more realistic energy losses and momentum transfers for dividing flow configurations. Data related to secondary flows provide information vital to bank stability, if the branch channel sides are erodible.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".