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Record W2074340555 · doi:10.1115/gt2004-53786

Measurements of Secondary Flows Downstream of a Turbine Cascade at Off-Design Incidence

2004· article· en· W2074340555 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsCarleton UniversityNational Research Council Canada
FundersNatural Sciences and Engineering Research Council of CanadaPratt and Whitney Canada
KeywordsMechanicsVortexInviscid flowAirfoilSecondary flowTrailing edgeCascadeInletLeading edgeTurbineUpstream (networking)Flow (mathematics)AerodynamicsPhysicsEngineeringAerospace engineeringTurbulenceMechanical engineering

Abstract

fetched live from OpenAlex

This paper presents experimental results of the secondary flows from two large-scale, low-speed, linear turbine cascades for which the incidence was varied. The aerofoils for the two cascades were designed for the same inlet and outlet conditions and differed mainly in their leading-edge geometries. Detailed flow field measurements were made upstream and downstream of the cascades and static pressure distributions were measured on the blade surfaces for three different values of incidence: 0, +10 and +20 degrees. The results from this experiment indicate that the strength of the passage vortex does not continue to increase with incidence, as would be expected from inviscid flow theory. The streamwise acceleration within the aerofoil passage seems to play an important role in influencing the strength of the vortex. The most recent off-design secondary loss correlation (Moustapha et al. [1]) includes leading-edge diameter as an influential correlating parameter. The correlation predicts that the secondary losses for the aerofoil with the larger leading-edge diameter are lower at off-design incidence; however, the opposite is observed experimentally. The loss results at high positive incidence have also high-lighted some serious shortcomings with the conventional method of loss decomposition. An empirical prediction method for secondary losses has been developed and will be presented in a subsequent paper.

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.

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 score0.811
Threshold uncertainty score0.376

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 head0.016
GPT teacher head0.210
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