MétaCan
Menu
Back to cohort
Record W2897114504 · doi:10.1139/tcsme-2018-0132

Nonlinear dynamics analysis of rotor-brush seal system

2018· article· en· W2897114504 on OpenAlexvenueno aff
Yuan Wei, Shulin Liu

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCritical speedBrushRotor (electric)VibrationNonlinear systemPhase portraitMechanicsHelicopter rotorControl theory (sociology)Seal (emblem)Structural engineeringEngineeringBifurcationPhysicsMechanical engineeringComputer scienceAcoustics

Abstract

fetched live from OpenAlex

When a gas turbine is working under high temperature, high pressure, and high velocity conditions, complex dynamic behavior and faults arise. These can seriously affect the security and reliability of the system, so it is important to further study nonlinear dynamic characteristics of the rotor-seal system. The seal force model of a brush seal was proposed, considering the interactions among bristle pack, flow force, and rotor, and a nonlinear dynamic model of the rotor-seal system was established. The influences of different geometries and operation parameters, such as rotor speed, installation spacing, damping, and rotor mass on the nonlinear characteristics of the system were discussed. The bifurcation scenario, vibration response, and stability of the rotor-seal system were analyzed by bifurcation diagram, time history, axis orbit, phase portrait, phase trajectory, Poincaré map, and frequency spectrum. The results showed that with a seal force the critical speed was greater than that without seal force conditions. The vibration amplitude of the rotor decreased with increase of damping and installation spacing. When the mass of the rotor increased, the vibration amplitude decreased significantly, which added stability to the rotor.

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: none
Teacher disagreement score0.944
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
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 head0.194
Teacher spread0.188 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicTribology and Lubrication EngineeringFrench-language works237,207