Large-eddy simulation of two-dimensional dunes in a steady, unidirectional flow
Bibliographic record
Abstract
We performed large-eddy simulations of the flow over a typical two-dimensional dune geometry at laboratory scale (the Reynolds number based on the average channel height and mean velocity is 18,900) using the Lagrangian dynamic eddy-viscosity subgrid-scale model. The results are validated by comparison with simulations and experiments in the literature. The flow separates at the dune crest, generating a shear layer that plays a crucial role in the transport of momentum and energy, and the generation of coherent structures. The turbulent kinetic energy budgets show the importance of the turbulent transport and mean-flow advection in the bulk flow above the shear layer. In the recirculation zone and in the attached boundary layers production and dissipation are the most important terms. Large, coherent structures of various types can be observed. Spanwise vortices are generated in the separated shear layer due to the Kelvin–Helmholtz instability; as they are advected, they undergo lateral instabilities and develop into horseshoe-like structures, are tilted downward, and finally reach the surface. The ejection that occurs between the legs of the vortex creates the upwelling and downdrafting events on the free surface known as “boils.” Near-wall turbulence, after the reattachment point, is affected by large streamwise Taylor–Görtler vortices generated on the concave part of the stoss side, which affect the distribution of the near-wall streaks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".