Design and characterization of the university of Toronto hybrid anechoic wind tunnel
Bibliographic record
Abstract
A detailed overview of the hybrid anechoic wind tunnel at UTIAS is presented, highlighting its design and performance features. The findings demonstrated that the tunnel achieves a uniform flow with very low turbulence intensity, matching the performance of similar open-loop wind tunnel facilities. The anechoic chamber effectively reduces noise with a cutoff frequency of around 160 Hz, providing a suitable environment for a broad spectrum of aeroacoustic measurements. The versatility of the wind tunnel was illustrated through its application in various aerodynamic and aeroacoustic studies, showcasing examples such as the NACA 0012 airfoil, the multi-element 30P30N configuration, and finite-span airfoil investigations. Moreover, the facility's Overall Sound Pressure Level (OASPL) is on par with other prominent global aeroacoustic wind tunnels, indicating its competitive performance and utility in the field. • Acoustic and Aerodynamic corrections were found for a hybrid anechoic wind tunnel. • The tunnel could achieve flow velocities between 10 and 60 m/s with a uniform flow. • Background noise levels were found to be on par with other facilities. • The anechoic cutoff frequency of the chamber was experimentally found to be 160 Hz. • The Kevlar loss was found to be below 2 dB in the frequency range of interest.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".