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Record W3199560012 · doi:10.1115/gt2021-58779

Influence of Stator Hub Cavities on the Forced Response Behaviour of an Embedded Compressor Rotor

2021· article· en· W3199560012 on OpenAlexaff
Shreyas Hegde, Robert E. Kielb, Laith Zori, Rubens Campregher

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsAnsys (Canada)
Fundersnot available
KeywordsGas compressorStatorLeakage (economics)Axial compressorAerodynamicsTurbomachineryRotor (electric)Labyrinth sealTurbineComputational fluid dynamicsInletEngineeringMechanical engineeringMechanicsControl theory (sociology)Automotive engineeringComputer scienceAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract This paper focuses on the impact of hub labyrinth seal leakage flows on the aeromechanical behavior of an embedded compressor rotor. End wall flows are critical in determining the performance of gas turbine engine compressors, particularly the hub leakage flows that can contribute to a significant reduction in performance due to the loss in efficiency induced by the leakage. While the current literature does contribute extensively to the understanding of the influence of this leakage flow on the steady compressor performance, no attention has been given to its impact on the multi-row unsteady aeromechanical influence. The authors of this paper have talked about the multi-row influence at various modes and operating condition using models without the hub cavities included [11–12;33–34]. The embedded compressor rotor utilized for this study is a part of a 3.5 stage subsonic rig located at the Zucrow Laboratory at Purdue University. The current paper first addresses the steady aerodynamics of a multi-row compressor with hub cavities and talks in detail about the effect of cavities on the performance at both the torsional mode and a higher order mode. Next the influence on the forcing function utilizing both 3-row (S1/R2/S2) and 4-row (S1/R2/S2/R3) simulations at both the Peak Efficiency (PE) and the High Loading (HL) operating conditions is determined. To reduce the computational domain significantly, the time transformation (TT) method was utilized within ANSYS CFX. The first part of the paper describes the multi-row influence of two neighboring stators having the same vane count, which excites the embedded rotor at the same resonant frequency; the second part shows the influence of having physical waves reflecting from a rotating row downstream (R3). The results show the significance of modelling the stator hub cavities and the drastic improvement in the modal force prediction with the cavities included. However, the authors observed that the impact tends to be more significant when the computational domain is small, i.e., fewer rows are included. As the number of rows are increased the influence of hub cavities diminish. Some of the conclusions drawn from this study are: 1) The presence of hub cavities changes the angle of incidence to the stators thereby reducing flow separation at the hub. The influence of these propagate throughout the domain i.e., a change in the angle of incidence in the first stage has an effect even at a downstream row. 2) The modal force prediction improved by ∼10% for the 3-row case and 1% for the 4-row case and the values moved closer to the experimental values in both cases. 3) The influence of hub cavities is more significant at torsional modes compared to higher order modes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.229

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 head0.008
GPT teacher head0.223
Teacher spread0.216 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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