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Record W1983081867 · doi:10.4271/2013-36-0551

Technical and Economic Advantages of Cold Forged Planetary-Bevel Gears Developed with Net Shape Teeth and Splines

2013· article· en· W1983081867 on OpenAlexaff
Juliano Savoy, Mauro Moraes de Souza, Tadeu Geraldo Domingues, Paulo César Sigoli

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2013
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsWeyerhauser (Canada)
Fundersnot available
KeywordsBevel gearNet (polyhedron)BevelMechanical engineeringEngineering drawingComputer scienceEngineeringStructural engineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">The search for more technical and economical competitive automotive products motivates even more the engineers to research for solutions that reduce manufacturing costs and lead-time. Bevel gears are applied extensively in the automotive industry since the invention of the transmission differential, however; few changes of the design have been done on these components in the last decades. Currently, the planetary-bevel gear blanks are hot forged with posterior cutting of the teeth and broaching of the spline, eventually, some planetary-bevel gear blanks have the teeth warm forged.</div><div class="htmlview paragraph">The process to cold forge the teeth and the splines results as much technically benefits for the product application as manufacturing costs and lead-time reductions.</div><div class="htmlview paragraph">This paper presents a planetary-bevel gears manufacturing concept for passenger and light commercial vehicles, where the cold forged teeth and splines present technical and economic benefits to the automotive differential transmission system.</div></div>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.209
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.

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
Published2013
Admission routes1
Has abstractyes

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