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Record W7108068711 · doi:10.1139/tcsme-2025-0015

Influence of surface elliptical dent defects on thermal elastohydrodynamic lubrication performance in ball-tripod universal joints

2025· article· en· W7108068711 on OpenAlexvenueno aff

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsnot available
FundersNatural Science Foundation of Shandong Province
KeywordsLubricationThermalEntrainment (biomusicology)Finite element methodJoint (building)Stress (linguistics)Tilt (camera)Surface (topology)

Abstract

fetched live from OpenAlex

Herein, the effects of elliptical dent defects on the properties of oil films formed in point-contact thermal elastohydrodynamic lubrication were examined through numerical modelling and ANSYS-based finite element analysis. Peak pressure and temperature of an oil film increase steeply with increasing depth on both sides of a dented edge, resulting in oil thickness variations across the dent and high stress concentration along the edge. Furthermore, peak pressure and temperature increase with the aspect ratio of elliptical dents, accompanied by shifts in subsurface stress directionality. Lubrication performance degrades with increasing dent direction angle and is the lowest when the dent’s long axis aligns with the entrainment direction. These findings highlight the detrimental effects of surface dents on joint lubrication performance.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.174
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

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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

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