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Record W1990181832 · doi:10.1115/1.1589028

Robustness of Rotating Stall Control for Axial-Flow Compressors*

2003· article· en· W1990181832 on OpenAlexaff
Ali Tahmasebi, Xiang Chen

Bibliographic record

VenueJournal of Dynamic Systems Measurement and Control · 2003
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsStall (fluid mechanics)Control theory (sociology)Axial compressorGas compressorRobustness (evolution)Nonlinear systemOperating pointComputer scienceEngineeringPhysicsMechanical engineeringControl (management)Aerospace engineering

Abstract

fetched live from OpenAlex

Feedback control has been pursued to address the rotating stall problem in axial flow compressors in order to extend the stable operating range and to improve engine performance. These controllers guarantee the stability of the bifurcated operating solution near the stall point. In this paper, an analytic approach is developed to characterize the robustness of some stabilizing controllers for rotating stall in axial-flow compressors. The numerical examples show that the size of the admissible uncertainty set changes for stabilizing controllers with different feedback gains. It is also proved that a nonlinear stabilizing control is not necessarily superior to a linear one.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.477

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 communication0.0000.000
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 head0.010
GPT teacher head0.195
Teacher spread0.185 · 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

Citations4
Published2003
Admission routes1
Has abstractyes

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