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Record W2796620566 · doi:10.1115/gt2014-27207

Effects of Area Ratio and Mean Rise Angle on the Aerodynamics of Inter-Turbine Ducts

2014· article· en· W2796620566 on OpenAlexafffund
Yanfeng Zhang, Shuzhen Hu, Ali Mahallati, Xuefeng Zhang, Edward Vlasic

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaPratt and Whitney Canada
KeywordsAdverse pressure gradientCasingMechanicsInletDuct (anatomy)Reynolds numberBoundary layerVortexFlow separationAerodynamicsTurbinePressure gradientMean flowMaterials scienceStatic pressureTurbulencePhysicsGeologyEngineeringMechanical engineeringThermodynamicsGeomorphology

Abstract

fetched live from OpenAlex

The present work, a continuation of a series of investigations on the aerodynamics of aggressive inter-turbine ducts (ITD), is aimed at providing detailed understanding of the flow physics and loss mechanisms in four different ITD geometries. A systematic experimental and computational study was carried out for varying duct mean rise angles and outlet-to-inlet area ratio while keeping the duct length-to-inlet height ratio, Reynolds number and inlet swirl constant in all four geometries. The flow structures within the ITDs were found to be dominated by the counter-rotating vortices and boundary layer separation in both the casing and hub regions. The duct mean rise angle determined the severity of adverse pressure gradient in the casing’s first bend whereas the duct area ratio mainly governed the second bend’s static pressure rise. The combination of upstream wake flow and the first bend’s adverse pressure gradient caused the boundary layer to separate and intensify the strength of counter-rotating vortices. At high mean rise angle, the separation became stronger at the casing’s first bend and moved farther upstream. At high area ratios, a 2-D separation appeared on the casing. Pressure loss penalties increased significantly with increasing duct mean rise angle and area ratio.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.004
GPT teacher head0.166
Teacher spread0.162 · 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

Citations4
Published2014
Admission routes2
Has abstractyes

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Same topicFluid Dynamics and Turbulent FlowsFrench-language works237,207