Experimental and Numerical Investigation of Bio-Inspired Airfoil Trailing-Edge Designs for Noise Reduction
Bibliographic record
Abstract
Embedded Large Eddy Simulations (ELES) are employed in tandem with the Ffowcs Williams-Hawkings (FW-H) aeroacoustic model to investigate the aerodynamics and tonal noise of NACA0012 airfoils having different bio-inspired noise-suppressing trailing-edge (TE) configurations.Various designs, such as standard sawtooth serrations, surface finlets, finned serrations and slanted-root sawtooth serrations are studied and compared.The different designs are shown to leverage different noise-suppressing flow mechanisms.The effects of changing standard serration amplitude and wavelength on the radiated tonal peak is studied.Experimental results suggest that noise reduction for surface finlets is dependent on the airfoil angle of attack.Slanted-root serrations are shown to alter the flow-field and suppress unwanted tonal peaks.ELES results are compared with experimental measurements, with good overall agreement.ELES is demonstrated to be a reasonable alternative to the currently-used more computationally demanding, full LES or direct numerical simulation approaches.𝜌𝑢 ∞ 𝐷 𝜇 , of approximately 500,000, where 𝜌 is the fluid density, 𝜇 is the dynamic Case RANS LES Total C1.1
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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 | 0.000 | 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) | 0.001 | 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".