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Record W2176134028 · doi:10.5539/mer.v5n2p114

The Influence of Design Parameters on Straight Bevel Gear Dynamics

2015· article· en· W2176134028 on OpenAlexvenueno aff
Chíu-Fan Hsieh, You-Qing Zhu

Bibliographic record

VenueMechanical Engineering Research · 2015
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBacklashSpiral bevel gearBevel gearPressure angleBevelStructural engineeringTorqueNon-circular gearDrive shaftEngineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

<p class="1Body">This study analyzes the influence of design parameters on the dynamics of straight bevel gears by constructing a model that allows variation in the shaft angle, pressure angle, and backlash. According to the statistical analysis, the order of influence of these parameters on weight is shaft angle > pressure angle > backlash. When the shaft angle is 90°, the statistical results show the drive is stable and the stress fluctuation level is low. The pressure angle, on the other hand, can affect the gear’s dynamic property by influencing the driving component force on the gear and the component force on the shaft. The results for the shaft and pressure angles are used to determine the appropriate backlash. Overall, the analysis not only provides designers with an important reference but explains the dominance in the market of gear designs with a 90° shaft angle and a 20° pressure angle.</p>

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.289
Teacher spread0.232 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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