Two-dimensional depth-averaged modeling of flow in curved open channels
Bibliographic record
Abstract
The application of the depth-averaged De St. Venant equations for open channel numerical models dictate the adoption of hydrostatic pressure distribution. They are thus applicable to cases where vertical details are not significant. The alternative two-dimensional vertically averaged and moment equations model, in which more vertical details are accounted for, is used to analyze problems involved in curved channels of various curvature. The distribution of horizontal velocity components is assumed to be linear, while the vertical velocity and pressure is quadratic. The implicit Petrov-Galerkin finite element scheme is used in these simulations. Computed values for water surface profile, depth-averaged longitudinal and transverse velocities across the channel width and vertical profiles of longitudinal and transverse velocities are compared with experimental data. The comparison shows a good agreement between the simulated results and experimental data. In addition, this study recommends the supplement of the standard conventional De St. Venant model by the proposed model on simulating strongly curved flows. Finally, the use of refined finite element meshes is recommended only when some of the details near the channel edges are sought.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".