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Record W4244967640 · doi:10.22215/etd/2015-12623

Controlling Secondary Flows in Highly-Loaded Compressor Cascades

2015· dissertation· en· W4244967640 on OpenAlexaff
Jean-Michel Prevost

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsCarleton University
Fundersnot available
KeywordsContouringSecondary flowCascadeGas compressorRotational symmetryKinetic energyMechanicsAerospace engineeringEnvironmental scienceMaterials scienceSimulationEngineeringPhysicsEngineering drawingClassical mechanics

Abstract

fetched live from OpenAlex

This thesis documents the experimental results of a research program investigating the effect of non-axisymmetric endwall contouring on the secondary flows and loss generation in a highly-loaded compressor cascade.The results are compared with the losses for the baseline flat endwall in order to evaluate the potential benefits.The compressor blade was designed by Pratt & Whitney Aircraft and is representative of an exit guide vane row in an aircraft engine.The experimental study was conducted in Carleton University's low speed linear cascade wind tunnel.The measurements were made at a constant Reynolds number of 150,000 (based on the axial chord and the inlet velocity) for two values of incidence, 0° (design incidence) and +7°.Quantitative results were obtained from static pressure measurements on the suction and pressure surfaces of the blade to evaluate the blade loadings and from measurements made by a seven-hole pressure probe downstream of the cascade to assess the blade row losses.Qualitative results were obtained from oil surface flow visualisation on the endwall and on the blade surfaces and were used to assist in the interpretation of the flow physics.The current research showed that the application of non-axisymmetric endwall contouring at design incidence modified the secondary flows near the endwall, mitigating the formation of the corner stall.The benefits from contouring were observed in terms of reductions in the secondary losses and in the underturning of the secondary flows compared to the flat endwall test case.However, these benefits were not observed at the off-design incidence studied.The application of endwall contouring generated higher secondary kinetic energy near the endwall, which penetrated deeper along the span and occupied a larger area, resulting in higher secondary and total losses as it dissipated moving downstream of the cascade.xiv WT Wind tunnel coordinate system

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.008
GPT teacher head0.230
Teacher spread0.221 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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