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Record W2044590964 · doi:10.1155/2007/56808

Active Suppression of Rotating Stall Inception with Distributed Jet Actuation

2007· article· en· W2044590964 on OpenAlexaff
Huu Duc Vo

Bibliographic record

VenueInternational Journal of Rotating Machinery · 2007
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsUniversité de MontréalPolytechnique Montréal
FundersAir Force Office of Scientific ResearchU.S. Air ForceMassachusetts Institute of Technology
KeywordsStall (fluid mechanics)Control theory (sociology)Computer scienceActuatorGas compressorFeedback controllerMechanicsPhysicsAerospace engineeringControl (management)Engineering

Abstract

fetched live from OpenAlex

An analytical and experimental investigation of the effectiveness of full-span distributed jet actuation for active suppression of long length-scale rotating stall inception is carried out. Detailed modeling and experimental verification highlight the important effects of mass addition, discrete injectors, and feedback dynamics, which may be overlooked in preliminary theoretical studies of active control with jet injection. A model of the compression system incorporating nonideal injection and feedback dynamics is verified with forced response measurements to predict the right trends in the movement of the critical pole associated with the stall precursor. Active control experiments with proportional feedback control show that the predicted stall precursors are suppressed to give a 5.5% range extension in compressor flow coefficient. In addition, results suggest that the proposed model could be used to design a more sophisticated controller to further improve performance while reducing actuator bandwidth requirements.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.244
Teacher spread0.238 · 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 designBench or experimental
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
Published2007
Admission routes1
Has abstractyes

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