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Record W2138579535 · doi:10.1115/1.4007833

Investigation of Streamwise and Transverse Instabilities on Swept Cylinders and Implications for Turbine Blading

2013· article· en· W2138579535 on OpenAlexfundno aff
J. P. Gostelow, Aldo Rona, Myriam de Saint Jean, Stephen Garrett, W. A. McMullan

Bibliographic record

VenueJournal of Turbomachinery · 2013
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsTransonicMechanicsVortexPhysicsInstabilityCylinderTransverse planeVorticityBoundary layerFlow visualizationKármán vortex streetTurbineOpticsFlow (mathematics)Classical mechanicsTurbulenceReynolds numberAerodynamicsGeometryMathematicsEngineeringStructural engineering

Abstract

fetched live from OpenAlex

The starting point for this investigation was the observation of robust streamwise streaks in flow visualization on the suction surfaces of blades in a turbine cascade at subsonic and transonic speeds. The spanwise wavelength of an array of streamwise vortices had been predicted and is here confirmed experimentally. Observations of streaks on unswept turbine blades and on circular cylinders confirmed these earlier predictions, providing a firm basis for referencing the new measurements of vortical behavior. The observations made it clear that the boundary layers are highly three dimensional. In this paper observations of streamwise and transverse instabilities on swept circular cylinders, over a range of inclinations, are presented. The circular cylinder is a canonical case and observations relate the streamwise vorticity of the unswept case to the more aggressive crossflow instability at high sweep angles. Introducing sweep brings consideration of a wide range of instabilities. Prominent is crossflow instability resulting from the inflectional behavior of a three-dimensional boundary layer.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.330

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 head0.012
GPT teacher head0.205
Teacher spread0.194 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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