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Record W3103085756 · doi:10.1007/s40544-020-0449-1

State of the art of friction modelling at interfaces subjected to elastohydrodynamic lubrication (EHL)

2020· article· en· W3103085756 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFriction · 2020
Typearticle
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsUniversity of Saskatchewan
FundersPurdue University
KeywordsLubricationReciprocating motionMaterials scienceLubricantViscosityBoundary lubricationMechanicsDeformation (meteorology)Mechanical engineeringComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Elastohydrodynamic lubrication (EHL) is a type of fluid-film lubrication where hydrodynamic behaviors at contact surfaces are affected by both elastic deformation of surfaces and lubricant viscosity. Modelling of contact interfaces under EHL is challenging due to high nonlinearity, complexity, and the multi-disciplinary nature. This paper aims to understand the state of the art of computational modelling of EHL by (1) examining the literature on modeling of contact surfaces under boundary and mixed lubricated conditions, (2) emphasizing the methods on the friction prediction occurring to contact surfaces, and (3) exploring the feasibility of using commercially available software tools (especially, Simulia/Abaqus) to predict the friction and wear at contact surfaces of objects with relative reciprocating motions.

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.

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: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.179
Teacher spread0.170 · 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