Numerical investigation of surface slip on turbulent flow around National Advisory Committee for Aeronautics 64-618 airfoil at high Reynolds number
Bibliographic record
Abstract
This study investigates the effect of surface slip on the unsteady vortex dynamics around the National Advisory Committee for Aeronautics (NACA) 64-618 airfoil using unsteady Reynolds-averaged Navier–Stokes simulation. The Reynolds number, based on the chord length and freestream velocity, was 1.3 × 106 and at an angle of attack of 12°. A Navier-slip boundary condition, modeled to mimic a superhydrophobic coating, was implemented on the walls of the airfoil to assess its impact on turbulent flow dynamics. Four slip lengths (Ls = 100 μm, Ls = 140 μm, Ls = 185 μm, and Ls = 400 μm) in addition to the base no-slip condition were examined. The spatiotemporal dynamics and the interactions between the small-scale Kelvin–Helmholtz vortices and the energetic large-scale von-Karman vortices are examined using frequency spectra and the proper orthogonal decomposition (POD). The mean flow topology revealed distinct separation bubbles at the trailing edge in the baseline no-slip case. Regardless of the slip length considered, suppression of the separation bubble was observed, resulting in greater acceleration of the flow in the wake region. Also, instantaneous flow visualization showed that the shear-layer instability was enhanced, causing an early vortex roll-up in the wake when the slip was imposed. Frequency analysis conducted along the separated shear layer further revealed the migration of dominant frequencies to the lower frequency range, especially for Ls = 400 μm. Based on the results from the POD analysis, it can be concluded that slip significantly increases the turbulent kinetic energy in the wake and concentrates this energy within the identified mode pairs.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".