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Record W2193810558 · doi:10.1115/1.4032164

Mistuned Forced Response Predictions of an Embedded Rotor in a Multistage Compressor

2015· article· en· W2193810558 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

VenueJournal of Turbomachinery · 2015
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsAnsys (Canada)
Fundersnot available
KeywordsGas compressorStatorRotor (electric)WakeAmplitudeAerodynamicsMechanicsTurbomachineryControl theory (sociology)PhysicsComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

This paper covers a comprehensive forced response analysis conducted on a multistage compressor and compared with the largest forced response experimental data set ever obtained in the field. The steady-state aerodynamic performance and stator wake predictions compare well with the experimental data, although losses are underestimated. Coupled and uncoupled unsteady simulations are conducted on the stator–rotor configuration. It is shown that the use of a decoupled method for forced response cannot yield accurate results for cases with strong inter-row interactions. The individual and combined contributions of the upstream and downstream stators are also assessed. The downstream stator is found to have a tremendous impact on the forced response predictions due to the constructive interactions of the two stator rows. Finally, predicted mistuned blade amplitudes are compared to mistuned experimental data. The average amplitudes match the experiments very well, while the maximum response amplitude is underestimated.

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)0.001
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: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.569

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 communication0.0000.001
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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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