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Record W4387144187 · doi:10.1115/gt2023-102198

Turbomachinery Transient Dynamics of Radial Rotor-Stator Contact Occurrences With Friction

2023· article· en· W4387144187 on OpenAlexaff
C. Jacobs, Mathias Legrand, Fabrice Thouverez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMagnetic Bearings and Levitation Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsStatorTurbomachineryRotor (electric)Control theory (sociology)StictionTransient (computer programming)MechanicsTransient responseTorquePhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract The present paper focuses on the numerical investigation of the transient response of a rotorshaft affected by unilateral contact occurrences with friction mechanisms. Rotor-stator contact is initiated radially at the shaft level. The components are modeled under the rigid bodies assumption and the rotor dynamical response is investigated in the time domain. The turbomachine is assumed to be driven by two torques: the first one is prescribed while the second one is induced by friction using Coulomb’s model. Particular attention is paid to the accurate prediction of the unknown rotational speed transient. The proposed methodologies are grounded on the Carpenter and Moreau-Jean time-marching algorithms, implying the use of Lagrange multipliers to solve the frictional and unilateral contact conditions. The simplest procedure considers only sliding friction while the most sophisticated one involves convex analysis in order to deal with normal and friction forces independently is case of stiction. The solutions predicted by the algorithms are compared and show good agreement. The sensitivity study on the stator properties and friction coefficient allows the identification of the conditions affecting the rotational speed limitation. Based on the response post-processing in the time and frequency domains, it is found that a higher friction coefficient, a stiffer stator support or a lighter stator leads to a decrease of the rotational speed maximum value.

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 score0.196
Threshold uncertainty score0.302

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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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
Published2023
Admission routes1
Has abstractyes

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