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Record W2102097051 · doi:10.1115/1.4003818

Effects of an Upstream Cavity on the Secondary Flow in a Transonic Turbine Cascade

2012· article· en· W2102097051 on OpenAlexaff
Hamza M. Abo El Ella, S. A. Sjolander, T. J. Praisner

Bibliographic record

VenueJournal of Turbomachinery · 2012
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsCarleton University
Fundersnot available
KeywordsTransonicMach numberCascadeMechanicsLeading edgeChord (peer-to-peer)Reynolds numberSecondary flowTrailing edgeTurbineWind tunnelPhysicsSubsonic and transonic wind tunnelGeometryAerospace engineeringAerodynamicsEngineeringMathematicsTurbulenceComputer science

Abstract

fetched live from OpenAlex

This paper examines experimentally the effects of an upstream cavity on the flow structures and secondary losses in a transonic linear turbine cascade. The cavity approximates the endwall geometry resulting from the platform overlap at the interface between stationary and rotating turbine blade rows. Previous investigations of the effects of upstream cavity geometries have been conducted mainly at low-speed conditions. The present work aims to extend such research into the transonic regime with a more engine representative upstream platform geometry. The investigations were carried out in a blow-down type wind tunnel. The cavity is located at 30 % of axial chord from the leading edge, extends 17 % of axial-chord in depth, and is followed by a smooth ramp to return the endwall to its nominal height. Two cascades are examined for the same blade geometry: the baseline cascade with a flat endwall and the cascade with the cavity endwall. Measurements were made at the design incidence and the outlet design Mach number of 0.80. At this condition, the Reynolds number based on outlet velocity is about 600,000. Off-design outlet Mach numbers of 0.69, and 0.89 were also investigated. Flowfield measurements were carried out at 40 % axial-chord downstream of the trailing edge, using a seven-hole pressure probe, to quantify losses and identify the flow structures. Additionally, surface flow visualization using an ultra-violet reactive dye was employed at the design Mach number, on the endwall and blade surfaces, to help in the interpretation of the flow physics. The experimental results also include blade-loading distributions, and the probe measurements were processed to obtain total-pressure loss coefficients, and streamwise vorticity distributions. It was found that the presence of the upstream cavity noticeably altered the structure and the strength of the secondary flow. Some effect on the secondary losses was also evident, with the cavity having a larger effect at the higher Mach number.

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)0.001
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 score0.466
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.200
Teacher spread0.196 · 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 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

Citations9
Published2012
Admission routes1
Has abstractyes

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