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Record W2045356673 · doi:10.1155/2012/928623

Encounters with Vortices in a Turbine Nozzle Passage

2012· article· en· W2045356673 on OpenAlexaff
J. P. Gostelow, Ali Mahallati, W. E. Carscallen, Aldo Rona

Bibliographic record

VenueInternational Journal of Rotating Machinery · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsVortexMechanicsPhysicsVorticityTransonicStarting vortexVortex sheddingSuctionHorseshoe vortexAirfoilTurbineWakeVortex ringMaterials scienceMeteorologyAerodynamicsThermodynamicsReynolds number

Abstract

fetched live from OpenAlex

Experiments were conducted on the flow through a transonic turbine cascade. Secondary flows and a wide range of vortex types were encountered, including horseshoe vortices, shock-induced passage vortices, and streamwise vortices on the suction surface. In the separation region on the suction surface, a large rollup of passage vorticity occurred. The blunt leading edge gave rise to strong horseshoe vortices and secondary flows. The suction surface had a strong convex curvature over the forward portion and was quite flat further downstream. Surface flow visualization was performed and this convex surface displayed coherent streamwise vorticity. At subsonic speeds, strong von Kármán vortex shedding resulted in a substantial base pressure deficit. For these conditions, time-resolved measurements were made of the Eckert-Weise energy separation in the blade wake. At transonic speeds, exotic shedding modes were observed. These phenomena all occurred in experiments on the flow around one particular turbine nozzle vane in a linear cascade.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.222
Teacher spread0.217 · 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 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

Citations16
Published2012
Admission routes1
Has abstractyes

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