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Record W2800627064 · doi:10.1139/tcsme-2016-0046

CALCULATION OF ADDITIONAL AXIAL FORCE OF ANGULAR-CONTACT BALL BEARINGS IN ROTOR SYSTEM

2016· article· en· W2800627064 on OpenAlexvenueno aff
Zhenhuan Ye, Zhansheng Liu, Liqin Wang

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsBall (mathematics)Bearing (navigation)Angular displacementNonlinear systemBall bearingRotor (electric)Contact forceRigid rotorHelicopter rotorDisplacement (psychology)Magnetic bearingMechanicsStructural engineeringControl theory (sociology)EngineeringPhysicsClassical mechanicsMechanical engineeringComputer scienceMathematicsMathematical analysisLubricationAcoustics

Abstract

fetched live from OpenAlex

Based on a loading-deformation relationship of bearing elements and the coordination of displacement between bearings in the rotor system, a model for calculating the additional axial force of angular-contact ball bearings in a single-rotor system is established. Nonlinear equations of this model are solved through the Rapid Descent method and Newton-Raphson method. The simulation results which are based on Gupta’s example verify that both the model and solving methods in this paper are reliable. A pair of 276927NK1W1(H) angular-contact ball bearings in symmetry in the single-rotor system is used as the example, calculation results of the additional axial force of bearings from the model in this paper and from the ISO method are compared and the influence of bearing geometry parameters and working conditions on the additional axial force is further studied. This model and its conclusions could provide the basic data and reference for analyzing the carrying ability and dynamic properties of rolling bearings.

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 score0.870
Threshold uncertainty score0.897

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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

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