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Record W2612177409 · doi:10.1155/2017/4120862

Active Flow Control in a Radial Vaned Diffuser for Surge Margin Improvement: A Multislot Suction Strategy

2017· article· en· W2612177409 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Rotating Machinery · 2017
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsUniversité de Sherbrooke
FundersOffice National d'études et de Recherches AérospatialesUniversité de Toulouse
KeywordsDiffuser (optics)MechanicsCentrifugal compressorSuctionReynolds-averaged Navier–Stokes equationsSurgeGas compressorBoundary layer suctionBoundary layerFlow (mathematics)Work (physics)Flow separationControl theory (sociology)Computational fluid dynamicsImpellerComputer sciencePhysicsMeteorologyThermodynamicsBoundary layer controlOptics

Abstract

fetched live from OpenAlex

This work is the final step of a research project that aims at evaluating the possibility of delaying the surge of a centrifugal compressor stage using a boundary-layer suction technique. It is based on Reynolds-Averaged Navier-Stokes numerical simulations. Boundary-layer suction is applied within the radial vaned diffuser. Previous work has shown the necessity to take into account the unsteady behavior of the flow when designing the active flow control technique. In this paper, a multislot strategy is designed according to the characteristics of the unsteady pressure field. Its implementation results in a significant increase of the stable operating range predicted by the unsteady RANS numerical model. A hub-corner separation still exists further downstream in the diffuser passage but does not compromise the stability of the compressor stage.

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.

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 score0.230
Threshold uncertainty score0.549

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 communication0.0000.001
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 head0.008
GPT teacher head0.255
Teacher spread0.247 · 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