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A notch methodology to estimate fretting fatigue strength

2007· article· en· W2152590687 on OpenAlexaff
Luiz Homero L. Martins, Júlio Cesar T. Ferro, J.L.A. Ferreira, José Alexander Araújo, Lucas Susmel

Bibliographic record

VenueJournal of the Brazilian Society of Mechanical Sciences and Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsTrinity College
Fundersnot available
KeywordsFrettingFatigue limitStructural engineeringMaterials scienceLimit (mathematics)Slip (aerodynamics)Fatigue testingWork (physics)BendingMechanicsComposite materialEngineeringMathematicsMathematical analysisMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

The aim of this work is to propose a methodology to estimate the fatigue limit of cylindrical contacts under a partial slip regime. Taylor’s point stress method, usually applied to estimate fatigue limit for notched structures, was associated with the Modified Wöhler Curves to define the fretting crack initiation threshold methodology. Twenty-nine tests on cylindrical contacts were selected from the literature and considered to evaluate the quality of the estimates. The results agree well for twenty-three experimental data. As the fatigue limit under fully reversed bending is the fatigue parameter usually available for most metallic alloys, it was also showed how the second fatigue limit needed to calibrate the proposed procedure could be estimated by taking full advantage from other standard predictive methodologies previously devised to estimate the mean stress effect under uniaxial fatigue loading.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
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
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.314
Teacher spread0.274 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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