Adding a simple production term to Reynolds-averaged Navier–Stokes turbulence models for flows over two-dimensional hills
Bibliographic record
Abstract
We consider an additional production term for the k,ε turbulence model that is activated by curvature, for turbulent flow over two-dimensional hills of varying steepness. The new term depends on the difference between the strain rate, S, and the rotation, R, which we refer to as the “SR” modification. It is compared to the standard k,ε turbulence model, the Kato–Launder model, and the re-normalization group and realizable versions of the k,ε model. The Kato–Launder model showed the best overall predictions for mean velocity, turbulent kinetic energy, and Reynolds shear stress at most locations before, on, and after the crest of the hills. The SR model was slightly less accurate but uniquely predicted the flow separation in the lee of the steeper hill and was also correctly predicted the flow re-attachment point. This study demonstrates the importance of including a curvature production term in k–ε-based models for flows over hills.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".