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Record W2521510677 · doi:10.1115/gt2016-56718

Experimental and Numerical Simulation of a Contact Induced Rotor/Stator Interaction Inside an Aircraft Engine High-Pressure Compressor

2016· article· en· W2521510677 on OpenAlexafffund
Alain Batailly, Quentin Agrapart, Antoine Millecamps

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsPolytechnique Montréal
FundersPolytechnique Montréal
KeywordsRubbingRotor (electric)StatorComputer simulationGas compressorAirfoilFocus (optics)Computer scienceMechanical engineeringEngineeringMechanicsSimulationStructural engineeringPhysicsOptics

Abstract

fetched live from OpenAlex

The development of a predictive numerical strategy for the simulation of rotor/stator interactions is a concern for several aircraft engine manufacturers. As a matter of fact, modern designs of aircraft engines feature reduced operating clearances between rotating and static components which yields more frequent structural contacts. Subsequent interaction phenomena (be it rubbing events, modal interaction or whirl motions) are not yet fully understood. For that reason, experimental data obtained from set-ups dedicated to the simulation of such interactions are scrutinized and are key in: (1) increasing the knowledge of the interaction phenomena and (2) allowing for a calibration of the numerical models with realistic events. In this contribution, the focus is made on an experimental set-up in Snecma facilities. It features a full-scale high-pressure compressor stage and aims at simulating contact induced interactions between one of the blades (slightly longer than the other ones) and the surrounding abradable coating that is deposited along the casing circumference. For this experimental set-up, it is found that the witnessed interaction involves a single blade — thus it should be analyzed as a sequence of rubbing events — and more specifically its first torsional mode, which is its second free-vibration mode. The focus is made both on the presentation of the experimental set-up and on the confrontation with the numerical results. Numerical results are analyzed by means of adaptative signal processing techniques and the consistency between numerical results and experimental observations is underlined both in time and frequency domains. In particular, the numerical strategy developed for Snecma is shown to predict very accurately the nature of the interaction as wear patterns obtained experimentally and numerically are a match. This numerical/experimental confrontation is the first attempt to calibrate a sophisticated numerical strategy with experimental data acquired within the high-pressure compressor of an aircraft engine for the simulation of rotor/stator interactions. Contrary to previous studies carried out within the low-pressure compressor of an aircraft engine, this interaction is found to be non-divergent: high amplitudes of vibration are experimentally observed and numerically predicted over a very short period of time. The ability of the numerical strategy to predict torsion induced interactions opens avenues for further analyses in turbine stages and with more sophisticated models including mistuned bladed disks and multi-stage components.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.388

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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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 designBench or experimental
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
Published2016
Admission routes2
Has abstractyes

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