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Record W2131217260 · doi:10.4271/2011-01-0489

Effects of Roller Diameter and Number on Fatigue Lives of Cam Roller Follower Bearings

2011· article· en· W2131217260 on OpenAlexaff
Jaewon Lee, Jwo Pan, Yung-Li Lee, Simon Ho

Bibliographic record

VenueSAE International Journal of Materials and Manufacturing · 2011
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsChrysler (Canada)
Fundersnot available
KeywordsAutomotive engineeringRoller bearingMaterials scienceStructural engineeringMechanical engineeringComposite materialEngineeringLubrication

Abstract

fetched live from OpenAlex

Effects of roller diameter and number on the contact pressures, subsurface stresses and the fatigue lives of cam roller follower bearings are investigated in this paper. Finite element analyses under plane strain conditions were conducted to identify the effects of the diameter and number of the rolling elements and the thickness of the outer ring. The fatigue life of the inner pin generally increases as the roller diameter increases. But, reducing the number of rollers to accommodate larger rollers does not necessarily increase the fatigue life. The inevitable decrease of the thickness of the outer ring due to the increase of the roller diameter results in the increase of compliance for the outer ring. This increase of compliance leads to excessive deformation of the outer ring and consequently more load must be carried by fewer number of rolling elements. For cam roller follower bearings, a parametric study based on the finite element analyses should be conducted to obtain the optimum geometry which gives the lowest contact pressure and maximum subsurface Mises stress which results in the longest fatigue life.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2011
Admission routes1
Has abstractyes

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