Turbulent Boundary Layer Trailing Edge Noise in the UTIAS Hybrid Anechoic Wind Tunnel
Bibliographic record
Abstract
The TBL-TE noise of the NACA 0012 airfoil model was investigated using the hybrid anechoic wind tunnel at UTIAS for a chord-based Reynolds number Re = 1.0 × 10^6. Surface pressure fluctuations near the trailing edge and the far-field acoustic signature were measured simultaneously. Initial comparisons of the collected data with analytical models and past experimental data show good agreement at low angles of attack. Using the modelled and measured data, comparisons between Amiet’s acoustic model and the measured farfield acoustic data are performed. Some agreement is achieved, though due to a low signal-to-noise ratio in the farfield acoustic measurements, comparisons are only drawn over small frequency ranges. Further work to better isolate the trailing-edge noise and to understand the other contaminating noise sources that may be present in the experimental facility are proposed for future work. Initial agreements in the nearfield pressure measurements with calculated models show promise for future work on insights at higher angles of attack that can be better captured in the hybrid anechoic wind tunnel.
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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 | 0.001 | 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) | 0.000 | 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 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".