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Record W2888866033 · doi:10.1115/gt2018-75232

Influence of Rotor-Stator Interaction and Reflecting Boundary Conditions on Compressor Forced Response

2018· article· en· W2888866033 on OpenAlexaff
Zhiping Mao, Shreyas Hegde, Tianyu Pan, Robert E. Kielb, Laith Zori, Rubens Campregher

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsAnsys (Canada)
FundersPurdue University
KeywordsStatorHarmonicsRotor (electric)Gas compressorForcing (mathematics)WakeReflection (computer programming)Boundary (topology)HarmonicControl theory (sociology)Modal analysisBoundary value problemAcousticsMechanicsPhysicsComputer scienceEngineeringMathematicsMechanical engineeringMathematical analysisVibrationVoltageElectrical engineering

Abstract

fetched live from OpenAlex

This paper focuses on the rotor forced response behavior in a 3.5-stage compressor rig. The aim is to provide an accurate prediction of forced response with the less computational effort. Previous research indicates that by reducing the computation domain from 7-row to a 3-row stator-rotor-stator (S1-R2-S2) configuration, the forcing function is over-predicted by 60%. To address this over prediction, an investigation of boundary conditions and a study with additional rows are conducted. The influence of reflecting boundary conditions on the blade modal force is studied by preventing wave reflection. Additionally, a 5-row simulation is studied to take an extra source of excitation force, the IGV row with the same blade count as the other stators, into consideration. Three conclusions were drawn from this study: 1) boundary reflection has a significant influence on unsteady simulation and the modal force, thus should be avoided by using mesh treatment up and down stream; 2) the IGV wake contributes to the forcing function and cannot be ignored; 3) the clocking feature of IGV, S1, and S2 leads to a transfer of energy from 1st harmonic to other higher harmonics. This research provides a guidance of forced response modeling and can be employed for industrial forced response analysis.

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)0.000
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 score0.115
Threshold uncertainty score0.247

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 communication0.0000.000
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 head0.013
GPT teacher head0.296
Teacher spread0.283 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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