Direct Numerical Simulation of Transitional Airfoil Noise
Bibliographic record
Abstract
A compressible direct numerical simulation (DNS) is conducted of a cambered airfoil at 0◦ angle of attack that is embedded in a wind-tunnel flow at a Reynolds number of Re c = 150, 000, based on the chord length, and at a Mach number of M = 0.25. Under these flow conditions, a long laminar boundary layer region develops on the airfoil suction side that separates and reattaches close to the trailing edge. This produces a complex acoustic source field, with essentially a flapping shear layer interacting with the trailing edge. The acoustic field radiated under these conditions shows close resemblance with the noise field generated by the laminar instability noise mechanism. The DNS domain comprises only the near field around the airfoil; the aerodynamic effect of the wind tunnel is included by using an appropriate set of inflow boundary profiles, a technique that has been used successfully in previous numerical incompressible airfoil studies. The acoustic far field is then computed from the near field solution, using the Ffowcs-Williams and Hawkings equations for a porous control surface and a solid surface. The porous Ffowcs-Williams Hawkings surface shows a better agreement with experimental data. Hydrodynamic and acoustic results are also compared with a DNS conducted of the same airfoil but with a trip, resulting in an attached suction side boundary layer. The difference on hydrodynamic field are discussed and analyzed. Amiet’s analogy is used for both cases and it gives a good overall prediction on farfield noise.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".