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Record W4282587439 · doi:10.2514/6.2022-2861

Wall-Resolved LES of a Linear Compressor Cascade with Moving Endwall

2022· article· en· W4282587439 on OpenAlexaff
Lorenzo Becherucci, Régis Koch, Stéphane Moreau

Bibliographic record

Venue28th AIAA/CEAS Aeroacoustics 2022 Conference · 2022
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsAdiabatic wallAerodynamicsCascadeMechanicsVortexAcousticsPhysicsNoise (video)Chord (peer-to-peer)Mach numberCompressible flowDirectivityLarge eddy simulationGas compressorCompressibilityBoundary layerTurbulenceEngineeringComputer science

Abstract

fetched live from OpenAlex

A wall-resolved compressible Large-Eddy Simulation has been performed on a linear compressor cascade with tip-gap with a moving end-wall and is compared to a stationary endwall configuration in order to study its effects on the aerodynamics and the noise generated by the tip-clearance flow. A new boundary condition has been implemented in the compressible Large Eddy Simulation code AVBP, and validated through the classic lid-driven cavity benchmark in order to obtain an adiabatic and viscous moving wall as boundary condition. The aerodynamic analysis has been coupled with the Ffowcs Williams and Hawkings acoustic analogy to compute the far-field noise and investigate the main noise sources related to the tip-clearance flow. This study provides the first wall-resolved compressible LES on a linear compressor cascade with a moving end-wall in order to investigate the noise related to the tip-leakage flow. Overall similar noise sources are found between the stationary and moving end-wall cases. Only the dipolar sound directivity is slightly shifted downstream with less marked lobes at high frequencies. Moreover, the noise source caused by the tip separation vortex at 6 kHz is slighty moved upward at 50% chord instead of 75% chord in the stationary end-wall case.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.492
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.207
Teacher spread0.192 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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