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Record W2169126166 · doi:10.1115/1.2184354

On Vortex Formation in the Wake Flows of Transonic Turbine Blades and Oscillating Airfoils

2005· article· en· W2169126166 on OpenAlexaff
J. P. Gostelow, Max F. Platzer, W. E. Carscallen

Bibliographic record

VenueJournal of Turbomachinery · 2005
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsNational Research Council Canada
FundersAir Force Office of Scientific Research
KeywordsWakeVortex sheddingAirfoilVortexTransonicStarting vortexPhysicsMechanicsTurbineTrailing edgeNozzleAerospace engineeringVortex ringAerodynamicsEngineeringTurbulenceReynolds number

Abstract

fetched live from OpenAlex

This paper demonstrates similarities between the vortex shedding from blunt trailing-edge transonic turbine nozzle blades and from oscillating airfoils and bluff bodies. Under subsonic conditions the turbine nozzle cascade shed wake vortices in a conventional von Kármán vortex street. This was linked with a depressed base pressure and associated energy separation in the wake. Under transonic conditions a variety of different shedding configurations was observed with vortices shedding and pairing in several different ways. Similarities are addressed between the observed structures and those from vortex shedding in some other physical situations, such as the vortex wakes shed from cylinders and airfoils in sinusoidal heaving motion in low-speed flow. The established field of vortex-induced vibration has provided a developed classification scheme for the phenomena observed. The paper has brought together three previously independent fields of investigation and, by showing that the three are essentially related, has provided the basis for a new synthesis.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.005
GPT teacher head0.207
Teacher spread0.202 · 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

Citations35
Published2005
Admission routes1
Has abstractyes

Explore more

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