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Record W1968061560 · doi:10.1115/gt2011-45189

Influence of Abradable Coating Wear Mechanical Properties on Rotor Stator Interaction

2011· preprint· en· W1968061560 on OpenAlexaff
Alain Batailly, Mathias Legrand, Christophe Pierre

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceCasingRotor (electric)CoatingStatorFinite element methodVibrationMechanicsComposite materialStructural engineeringMechanical engineeringAcoustics

Abstract

fetched live from OpenAlex

In the field of turbomachines, better engine performances are achieved by reducing possible parasitic leakage flows through the closure of the clearance distance between blade tips and surrounding casings. Accordingly, direct contact is now commonly accepted as part of aircraft engines everyday life. In order to avoid possibly catastrophic scenarii due to high contact forces between the rotating and static components, implementation of abradable coatings has been widely recognized as a robust solution offering several advantages: reducing potential damage to the incurring blade as well as adjusting operating clearances, in-situ, to accept physical contact events. In the present work, macroscopic behavior of the abradable coating is numerically approximated through a piecewise linear plastic constitutive law which allows for real time access to the current abradable layer profile. Contact simulations are carried out considering a three-dimensional industrial finite element model of a blade from a compressor stage and its surrounding casing, assumed perfectly rigid. Due to the large number of degrees of freedom, component mode synthesis methods are used. Simulations are repetitively carried-out over a wide rotational velocity range, and a large number of distinct values for two mechanical parameters of the abradable material are considered. Results show that the amplitude of vibration is highly sensitive to the Young modulus and the plastic modulus of the abradable and that a local maximum is detected. Also, a more realistic description of the contact forces allowing for a contribution in the tangential direction is suggested.

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 score0.772
Threshold uncertainty score0.710

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 integrity0.0000.001
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 head0.026
GPT teacher head0.224
Teacher spread0.198 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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