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Record W3088039399 · doi:10.33737/gpps20-tc-54

Aerodynamic Investigation of a Linear Compressor Cascade with Tip Gap Using Large-Eddy Simulation

2020· article· en· W3088039399 on OpenAlexafffund
Régis Koch, Marlène Sanjosé

Bibliographic record

VenueProceedings · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsÉcole de Technologie Supérieure
FundersCompute Canada
KeywordsMechanicsVortexBoundary layerCascadeAirfoilAerodynamicsLeakage (economics)TurbulenceChord (peer-to-peer)Reynolds numberMach numberBoundary layer suctionFlow separationPhysicsMaterials scienceAerospace engineeringBoundary layer controlEngineeringComputer science

Abstract

fetched live from OpenAlex

The flow in a linear compressor cascade with tip gap is simulated using a wall-resolved compressible Large-Eddy Simulation. The cascade is based on the Virginia Tech Low Speed Cascade Wind Tunnel. The Reynolds number based on the chord is 3.88 10 5 and the Mach number is 0.07. The gap considered in this study is 4.0 mm (2.9% of axial chord). An aerodynamic analysis of the tip-leakage flow allow us identifying the main mechanisms responsible for the development and the convection of the tip-leakage vortex downstream of the cascade. A region of high turbulence and vorticity levels is located along an ellipse that borders the top of the tip-leakage vortex. The influence of the airfoil suction side boundary layer development on the tip-leakage vortex is highlighted by tripping the flow. A tripped boundary layer induces a stronger and larger tip-leakage vortex that tends to move further away from the airfoil suction side and from the endwall compared with an untripped flow. The boundary layer turbulent state influences the tip-leakage flow development.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.498

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 head0.027
GPT teacher head0.230
Teacher spread0.203 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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