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Record W2314570322 · doi:10.1299/kikaia.79.1122

Production of Sintered Bearing by Unification Powder Forming from Different Metals Powder

2013· article· en· W2314570322 on OpenAlexaff
Toshihiko MOURI, Yousuke SUGAI, Makoto SHIRANAMI, Fuminori SATOJI, Mitsuo ARASHIDA, Eiji Yuasa

Bibliographic record

VenueTRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series A · 2013
Typearticle
Languageen
FieldEngineering
TopicPowder Metallurgy Techniques and Materials
Canadian institutionsFédération des Comités de Parents du Québec
Fundersnot available
KeywordsMaterials scienceSinteringElectron microprobeMetallurgyBearing (navigation)Composite numberLayer (electronics)DiffusionComposite material

Abstract

fetched live from OpenAlex

To develop the composite journal bearings (CJB) with high strength and high wear resistance, two different mixed powders were compacted in the shape of a double-layers cylinder. A mixed powder of Fe-Cu was used for an outer layer as back-up material. In inner layer, the mixed powder of Fe-Ni-Mo-Cu was used for wear resistance. The compacted cylindrical bearing was sintered at various temperatures. EPMA analysis was conducted to identify the distribution of elemental composition near the interface between the inner and outer layers. As a result, it was confirmed that the joining between the inner and outer layers in the CJB was achieved by a diffusion mechanism and the hardness increased with increasing the sintering temperature. After the sizing process, the CJB became higher circularity than journal bearing made by conventional P/M process.

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)0.000
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.197
Teacher spread0.187 · 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
Published2013
Admission routes1
Has abstractyes

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Same venueTRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series ASame topicPowder Metallurgy Techniques and MaterialsFrench-language works237,207