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Record W7132906065

The Measurement and Application of Trailing-Edge Noise in the UTIAS Hybrid Anechoic Wind Tunnel

2024· dissertation· W7132906065 on OpenAlexaboutno aff
Reuben William Haklander

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsnot available
Fundersnot available
KeywordsAirfoilAnechoic chamberWind tunnelAerodynamicsNoise (video)Angle of attackAeroacousticsNACA airfoilBoundary layer
DOInot available

Abstract

fetched live from OpenAlex

Turbulent boundary layer trailing-edge noise is a fundamental aeroacoustic noise source present in a variety of applications, including aircraft geometries, fans, and wind turbine blades. Understanding and controlling the source mechanisms of trailing-edge noise is an area of ongoing experimental research. In this work, trailing-edge noise has been applied as a benchmark noise case for a hybrid anechoic wind tunnel, an example of which has been recently constructed at the University of Toronto. This facility type is expected to offer advantages in replicating conditions for aeroacoustic sources at high angles of attack. The aerodynamic capabilities of the facility are demonstrated by measuring and analyzing the lift characteristics and boundary layer properties of a tripped two dimensional NACA 0012 airfoil at angles of attack between 0 and 15 degrees and freestream velocities between 20 and 50 m/s. The acoustic performance is then shown by comparing analytical models for the surface pressure fluctuations and far-field acoustic signature with measurements of the airfoil at zero degrees angle of attack. These comparisons reveal that trailing-edge source mechanisms are successfully produced and measured. However, spurious junction noise and background noise sources make isolation of the far-field acoustic signature challenging, suggesting some modifications that would further improve the hybrid tunnel's capabilities. Further acoustic characteristics of the facility are investigated using the Aeolian tone from a cylinder and a monopole point source from laser induced plasma, indicating satisfactory performance. Trailing-edge noise results are then extended to higher angles of attack, where the hybrid wind tunnel's ability to maintain expected flow conditions is demonstrated. Thicker boundary layers are observed, producing changes in the noise mechanisms as the airfoil approaches separation and stall. Investigations of the surface pressure fluctuations and acoustic signature reveal a shift to lower frequencies and an increase in noise amplitude due to the dominance of larger structures in the airfoil boundary layer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.273
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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