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Record W2088592000 · doi:10.1115/gt2011-45222

Effect of the Axial Spacing Between Vanes and Blades on the Performance of a Transonic Axial Turbine

2011· article· en· W2088592000 on OpenAlexafffund
Dongil Chang, Stavros Tavoularis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaPratt and Whitney Canada
KeywordsMach numberTransonicWakeChord (peer-to-peer)MechanicsAxial compressorStatorTurbineTurbulenceSupersonic speedMaterials scienceTurbine bladePhysicsStructural engineeringAerodynamicsGas compressorEngineeringThermodynamicsComputer science

Abstract

fetched live from OpenAlex

Unsteady numerical simulations have been conducted to investigate the effect of axial spacing between the stator vanes and the rotor blades on the performance of a transonic, single-stage, high-pressure, axial turbine. Three cases were considered, the reference case, which is based on the geometry of a commercial jet engine and has an axial spacing at 50% blade span equal to 42% of the vane axial chord, as well as two other cases with axial spacings equal to 31 and 52% vane axial chords, respectively. Present interest has focused on the effect of axial gap size on the instantaneous and time-averaged flows as well as on the blade loading and the turbine performance. Decreasing the gap size reduced the pressure and increased the Mach number in the core flows in the gap region. However, the flows near the two endwalls did not follow monotonic trends with the gap size change; instead, the Mach numbers for both the small gap and the large gap cases were lower than that for the reference case. This Mach number decrease was attributed to increased turbulence due to the increased wake strength for the small gap case and the increased wake width for the large gap case. In all considered cases, large pressure fluctuations were observed in the front region of the blade suction sides. These pressure fluctuations were strongest for the smaller spacing. The turbine efficiencies of the cases with the larger and smaller spacings were essentially the same, but both were lower than that of the reference case. The stator loss for the smaller spacing case was lower than the one for the larger spacing case, whereas the opposite was true for the rotor loss.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.190

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 head0.008
GPT teacher head0.184
Teacher spread0.176 · 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 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

Citations3
Published2011
Admission routes2
Has abstractyes

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