Restricted nonlinear simulations of flow over riblets: Characterizing drag reduction and its breakdown
Bibliographic record
Abstract
The restricted nonlinear (RNL) model is employed as low-order representation of turbulent flow over riblets at R e τ ≈ 395 . Comparisons with direct numerical simulations (DNS) verify the ability of the model to accurately capture low-order statistics, as well as trends in drag-alteration and secondary motion as a function of riblet geometry and spacing. We demonstrate the ability of the RNL model to reproduce additional flow features by decomposing the roughness function to isolate contributions from the total stress and comparing its predictions to DNS data. An analysis of the spectra of Reynolds shear stress shows that the RNL model captures Kelvin-Helmholtz-like rollers linked to riblet drag reduction breakdown but slightly over predicts the total stresses. The reproduction of the overall trends in stresses and flow features linked to the breakdown of riblet induced drag-reduction suggests that the nonlinearity and scale interactions retained in the RNL system are adequate to capture the key mechanisms underlying turbulent flow over a range of riblet geometries. These results also indicate that examining the limitations of the model may provide insight into the critical nonlinear interactions underlying drag alteration due to riblets .
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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 | 0.000 | 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".