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Record W2070537981 · doi:10.1299/jfst.4.138

Blade Vortex Interactions: Experimental Measurements of the Near-Flow Field

2009· article· en· W2070537981 on OpenAlexafffund
Yasser Aboelkassem

Bibliographic record

VenueJournal of Fluid Science and Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVortexStarting vortexMechanicsPhysicsVortex generatorVortex ringHorseshoe vortexBurgers vortexVortex stretchingRADIUSCore (optical fiber)Circulation (fluid dynamics)Optics

Abstract

fetched live from OpenAlex

The near-field flow structure of an intense streamwise vortex filament encountering normally with a blade tip vortex was investigated experimentally. Three cases were investigated, direct impingement, interactions on the pressure side and interactions over the suctions side. The effects of blade-vortex interaction were found to be strongly dependent on whether the vortex filament passed over the pressure or suction side of the blade. In case of, zero vortex-blade tip separation (direct impingement), the peak tangential velocity and total circulation of the interaction vortex remained basically unchanged, regardless of downstream distance, but had values larger than the generator vortex, while the core circulation and the core radius increased almost linearly with downstream distance, similar to an undisturbed generator vortex. The maximum total turbulent energy decreased as x/c increased. In summary, the present experiment deals with the normal interactions of streamwise vortex with another tip vortex shed by a blade end-tip, and focuses on the resultant vortex structures and peak values due to the interaction itself.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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
Published2009
Admission routes2
Has abstractyes

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