MétaCan
Menu
Back to cohort
Record W2514613828 · doi:10.5220/0005975500750083

Passivity-based Control of Surge and Rotating Stall in Axial Flow Compressors

2016· article· en· W2514613828 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

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsÉcole de Technologie SupérieurePolytechnique Montréal
Fundersnot available
KeywordsStall (fluid mechanics)SurgeAxial compressorControl theory (sociology)PassivityGas compressorComputer scienceMechanicsGeologyEngineeringPhysicsControl (management)Electrical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

In this work, we address the stability of compression systems and the active control of performance limiting phenomena: surge and rotating stall. Despite considerable efforts to stabilize axial compressors at efficient operating points, preventing and suppressing rotating stall and surge are still challenging problems. Due to certain passivity properties of the widely used Moore and Greitzer model for axial compressors, a robust passivity-based control approach is applied here to tackle the problem. The main advantage of this approach is that robust stabilization and high performance control can be achieved by simple control laws and limited control efforts. Analytical developments and time-domain simulations demonstrate that the developed control laws can effectively damp out rotating stall and surge limit cycles by throttle and close-coupled valve actuations. The robust performance of the controller is validated in the presence of bounded mass flow and pressure disturbances, as well as model uncertainties.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.053
GPT teacher head0.331
Teacher spread0.278 · 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