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Record W3123715913 · doi:10.22215/etd/2018-12858

The Design, Fabrication, and Commissioning of a High-Speed Aeroacoustic Wind Tunnel for Studies of Surface Pressure Fluctuations Beneath Turbulent Boundary Layers

2018· dissertation· en· W3123715913 on OpenAlexaboutno aff
Frank Giardino

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsnot available
Fundersnot available
KeywordsWind tunnelHypersonic wind tunnelTurbulenceBoundary layerSupersonic wind tunnelEngineeringMach numberWind speedDuct (anatomy)AerodynamicsAerospace engineeringWind gradientBoiler blowdownStatic pressureMarine engineeringComputational fluid dynamicsTransonicMechanical engineeringMeteorologyWind profile power lawInletPhysics

Abstract

fetched live from OpenAlex

The High-Speed Aeroacoustic Wind Tunnel (HSAWT) at Carleton University is a newly commissioned facility with the purpose of facilitating experimental studies of Turbulent Boundary Layer (TBL) induced surface pressure fluctuations. This research is intended for applications regarding aircraft noise generation from structures exposed to high-speed flow. This open-jet, blowdown facility is unique in Canada and one of a few aeroacoustic wind tunnels in the world capable of achieving speeds up to Mach 0.8.The details of the complete design and fabrication methodology for all wind tunnel duct components, control system hardware, and instrumentation systems is discussed; along with the numerical simulations performed in the validation of the designed components. Preliminary experimental flow measurements and characterization of the wind tunnel control system is examined. The results of initial measurements of TBL surface pressure fluctuations developed over a flat test section plate are compared with established data and empirical models in literature.

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)0.002
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.269
Teacher spread0.248 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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Same topicAerodynamics and Acoustics in Jet FlowsFrench-language works237,207