Benchmark of computational hydraulics models for open-channel flow with lateral cavities
Bibliographic record
Abstract
Computational models in hydro-environmental engineering are diverse in their background formulation and span from two-dimensional depth-averaged shallow water models, to complex fully three-dimensional turbulence models resolving large-eddy simulation with surface capturing techniques, and to Lagrangian particle-based methods. This paper presents a first-of-its-kind comparison of six different computational hydraulics fluid dynamics models, namely Iber+, HO-SWM, GBVC, OpenFOAM (RANS), Hydro3D (LES) and DualSPHysics (SPH), in the prediction of mean velocities and free-surface dynamics in two benchmarks involving open-channel flows with symmetric lateral cavities. Results show that shallow-water models capture relatively well the main large-scale coherent structures of the in-cavity flow, with wider shear layers compared to three-dimensional models, and higher velocities in the main channel. Three-dimensional RANS, LES and SPH yield improved predictions of mean velocities compared with experimental data. Computational cost has been quantified for all models with a logarithmic growth when increasing model complexity. The transverse standing wave is captured by most models, with the shallow-water ones matching the theoretical value, while the three-dimensional models overestimate it slightly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".