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Record W2052556749 · doi:10.1115/gt2003-38592

Aerodynamic and Aeroacoustic Performance of a Skewed Rotor

2003· article· en· W2052556749 on OpenAlexaff
Na Cai, Jianzhong Xu, A. Benaïssa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsAerodynamicsWakeStall (fluid mechanics)Mechanical fanAcousticsAnechoic chamberBoundary layerMach numberNoise (video)Rotor (electric)Noise reductionMechanicsEngineeringStructural engineeringPhysicsMechanical engineeringComputer science

Abstract

fetched live from OpenAlex

This paper presents an experimental investigation and numerical simulation of the aerodynamic and aeroacoustic performance of an axial-flow fan with skewed rotating blades in the design and off-design operation. The blade is designed with a forward skew angle for which the stacking line is directed towards the rotating direction on the circumferential section. A detailed investigation of a three-dimensional flow field in the inter-blade row and passage using five-hole probes and a hot-wire anemometer at the upstream and downstream locations of the rotors has been carried out and compared with a fan with unskewed rotor blades. Noise testing was performed in the anechoic chamber. The experiments were performed at three rotating speeds. Aerodynamic curves show that the performance of the skewed blade increased at a higher pressure rise of 13.1% and gave a larger flow rate of about 5% and a higher efficiency of more than 3%. The higher efficiency in the skewed rotor was due to the practical and advantageous spanwise redistribution of aerodynamic parameters, a greater boundary movement into the main flow, a secondary flow reduction and the thinness of the rotor wake. Aeroacoustic performance and frequency spectra in almost the whole frequency domain showed a noise reduction of 2 to 4 dBA in the skewed fan. Lower noise in the skewed blade comes from the broadband noise reduction owing to a thinner wake layer, a phase difference in rotor radiation and tip leakage noise reduction. A wider stall margin for more than 20% is obtained in the skewed blade due to the proportional distribution of aerodynamic parameters. The three-dimensional Navier-Stokes approach is simulated in the inner blade flow.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.003
GPT teacher head0.160
Teacher spread0.157 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations10
Published2003
Admission routes1
Has abstractyes

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