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Record W2113221197 · doi:10.1115/1.4006319

Aerodynamics of a Low-Pressure Turbine Airfoil at Low Reynolds Numbers—Part I: Steady Flow Measurements

2012· article· en· W2113221197 on OpenAlexaff
Ali Mahallati, Brian McAuliffe, S. A. Sjolander, T. J. Praisner

Bibliographic record

VenueJournal of Turbomachinery · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsCarleton UniversityNational Research Council Canada
Fundersnot available
KeywordsAirfoilFreestreamReynolds numberTurbulenceMechanicsTurbulence kinetic energyPhysicsBubbleLaminar flowFlow separationBoundary layer

Abstract

fetched live from OpenAlex

This two-part paper presents a detailed experimental investigation of the laminar separation and transition phenomena on the suction surface of a high-lift low-pressure turbine airfoil, PakB. The first part describes the influence of Reynolds number, freestream turbulence intensity and turbulence length scale on the PakB airfoil under steady inflow conditions. The present measurements are distinctive in that a closely-spaced array of hot-film sensors has allowed a very detailed examination of the suction surface boundary layer behavior. In addition, this paper presents a technique for interpreting the transition process in steady, and periodically unsteady, separated flows based on dynamic and statistical properties of the hot-film measurements. Measurements were made in a low-speed linear cascade facility at Reynolds numbers between 25,000 and 150,000 at three freestream turbulence intensity levels of 0.4%, 2%, and 4%. Two separate grids were used to generate turbulence intensity of 4% with integral length scales of about 10% and 40% of the airfoil axial chord length. While the higher levels of turbulence intensity promoted earlier transition and a shorter separation bubble, turbulence length scale did not have a noticeable effect on the transition process. The size of the suction side separation bubble increased with decreasing Reynolds number, and under low freestream turbulence levels the bubble failed to reattach at low Reynolds numbers. As expected, the losses increased with the length of the separation bubble, and increased significantly when the bubble failed to reattach.

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: Observational · Consensus signal: none
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 studies0.0010.001
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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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 designObservational
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

Citations47
Published2012
Admission routes1
Has abstractyes

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