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Record W2986775254 · doi:10.1139/tcsme-2019-0202

Contact fatigue model and life prediction of the compound motion curve-face gear pair

2019· article· en· W2986775254 on OpenAlexvenueno aff
Chao Lin, Peilu Li, Chunjiang He, Qingkun Xing

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTooth surfaceFace (sociological concept)Rotation (mathematics)PinionStructural engineeringContact mechanicsMotion (physics)Instant centre of rotationMachiningEngineeringFinite element methodMechanical engineeringGeometryComputer scienceMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Different from the common face gear pair fixed rotation motion between intersecting axes, the compound transmission of the curve-face gear is a new motion form, which can convert rotational motion into rotation and movement motion. To solve the contact fatigue life problem of this new motion form gear pair, a new contact fatigue life calculation method of the compound transmission curve-face gear pair was proposed. Based on the space gear engagement principle and the fracture mechanics theory, the theoretical contact fatigue model of the curve-face gear composite transmission was established. Considering that the contact load for every tooth is time-varying in the half-period of the curve-face gear, the contact fatigue life stage of the curve-face gear was divided into crack initiation and crack growth, and the crack growth fatigue life for each tooth was calculated using the finite element method. The curve-face gear pair was processed in the five-axis NC machining center and the compound transmission experiment platform of the curve-face gear was set up to measure the tooth surface dynamic contact stress, and the overall life of the curve-face gear was predicted. The comparison analysis between theoretical and experimental results verified the correctness of the theoretical contact fatigue calculation model.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.595
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.013
GPT teacher head0.184
Teacher spread0.171 · 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 designSimulation or modeling
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

Citations6
Published2019
Admission routes1
Has abstractyes

Explore more

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