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Record W2173440581 · doi:10.1115/gt2006-90280

Dynamic Properties of Tilting-Pad Journal Bearings: Experimental and Theoretical Investigation of Frequency Effects Due to Pivot Flexibility

2006· article· en· W2173440581 on OpenAlexaff
Waldemar Dmochowski

Bibliographic record

VenueVolume 5: Marine; Microturbines and Small Turbomachinery; Oil and Gas Applications; Structures and Dynamics, Parts A and B · 2006
Typearticle
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBearing (navigation)StiffnessInertiaFlexibility (engineering)Rotor (electric)Materials scienceExcitationFrequency domainTurbulenceMechanicsStructural engineeringAcousticsMechanical engineeringEngineeringComputer sciencePhysicsComposite materialElectrical engineeringClassical mechanicsMathematics

Abstract

fetched live from OpenAlex

Tilting-pad journal bearings (TPJB) dominate as rotor supports in high speed rotating machinery. The paper analyzes frequency effects on the TPJB’s stiffness and damping characteristics based on experimental and theoretical investigations. The experimental investigation has been carried out on a five pad tilting-pad journal bearing of 98 mm in diameter. Time domain and multifrequency excitation has been used to evaluate the dynamic coefficients. The calculated results have been obtained from a three-dimensional computer model of TPJB, which accounts for thermal effects, turbulent oil flow, and elastic effects, including that of pad flexibility. The analyzes of the TPJB’s stiffness and damping properties showed that the frequency effects on the bearing dynamic properties depend on the operating conditions and bearing design. It has been concluded that the pad inertia and pivot flexibility are behind the variations of the stiffness and damping properties with frequency of excitation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.841

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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 designObservational
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

Citations6
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueVolume 5: Marine; Microturbines and Small Turbomachinery; Oil and Gas Applications; Structures and Dynamics, Parts A and BSame topicTribology and Lubrication EngineeringFrench-language works237,207