MétaCan
Menu
Back to cohort
Record W2670956424 · doi:10.2497/jjspm.62.371

Strength and Friction-Wear Properties of Complex Layer Bearing via Unification Powder Forming and Sintering Process

2015· article· en· W2670956424 on OpenAlexaff
Toshihiko MOURI, Yousuke SUGAI, Y. Ito, Eiji Yuasa

Bibliographic record

VenueJournal of the Japan Society of Powder and Powder Metallurgy · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMetal Alloys Wear and Properties
Canadian institutionsFédération des Comités de Parents du Québec
Fundersnot available
KeywordsMaterials scienceBearing (navigation)Hardening (computing)SinteringMetallurgyComposite materialLayer (electronics)Vickers hardness testComposite numberMicrostructure

Abstract

fetched live from OpenAlex

The composite journal bearings which have outer layer with high strength and inner layer with high wear resistance can be used as bearing materials in the industrial high-power machine. The complex layer bearing prepared by unification forming of two different mixed powders with Fe-Cu-C in outer layer and Fe-Cu-C-Ni-Mo in inner layer, and then it was sintered for various heating times at 1378 K~1403 K. Mechanical properties of the bearing were investigated by determinations of Vickers hardness and radial crushing strength. The radial crushing strength of sintered bearing with outer layer composition of Fe-Cu-C mixed powder is increased by the addition of phosphorus of 0.2~0.6 weight% (Specimen F). Nevertheless the apparent density of this complex bearing is low. The friction and wear properties in this bearing also were estimated. The sliding property to hardening steel shaft of the complex layer bearing was invested by swing-type sliding machine. Wear loss volume of Specimen F is low under high applied load it is very suitable for use of the industrial high-power machine.

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.063
GPT teacher head0.263
Teacher spread0.200 · 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 teacher head, 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Japan Society of Powder and Powder MetallurgySame topicMetal Alloys Wear and PropertiesFrench-language works237,207