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Record W2063546502 · doi:10.1080/05698190490493382

An Investigation of the Steady-State Performance of a Pivoted Shoe Journal Bearing with ISO VG 32 and VG 68 Oils

2004· article· en· W2063546502 on OpenAlexaff
K. Brockwell, Waldemar Dmochowski, Scan M. DeCamillo

Bibliographic record

VenueTribology Transactions · 2004
Typearticle
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBearing (navigation)Steady state (chemistry)EngineeringAeronauticsForensic engineeringGeologyEnvironmental scienceMechanicsPhysicsChemistryAstronomy

Abstract

fetched live from OpenAlex

This article presents a report on an investigation into the performance characteristics of a steadily loaded pivoted shoe journal (PSJ) bearing that is lubricated with ISO VG 32 and VG 68 oils. The article describes a testing machine on which the experimental investigation was performed. Measurements of shaft torque, pad temperature distributions, oil inlet and outlet temperatures, oil flow rate, and eccentricity have all been recorded as functions of load and speed. The experimental results from both test oils are presented in graphical form and are compared with theoretical predictions obtained from the author's computer model of the PSJ bearing. These results showed that the thicker ISO VG 68 oil provided thicker oil films. However, it also had higher bearing temperatures and power losses. A good correlation between the theoretical and experimental results has been found. Theoretical analysis of the bearing friction losses indicate that shear losses predominate and churning losses account for approximately 20% of the total losses.

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)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.192
Teacher spread0.184 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

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