THE DESIGN AND MESHING EFFICIENCY ANALYSIS OF HELICAL SPUR GEAR REDUCER WITH SINGLE GEAR PAIR FOR ELECTRIC SCOOTERS
Bibliographic record
Abstract
To achieve reduced costs and energy conservation, this paper proposes non-standard helical spur gear reducer with one gear pair (having reduction ratio 19.25) to be the gear reducer for electric scooter. This paper also focuses on the meshing efficiency analysis of non-standard helical spur gear pair. According to Buckingham’s research, the theoretical meshing efficiency formula of non-standard helical spur gear pair is derived. Three design cases of non-standard helical spur gear pair (4, 77) are proposed as examples for analyzing their meshing efficiencies at widely rotation speed range. The theoretical meshing efficiencies for the helical spur gear pair (4, 77) are between 96.47–99.26%. Its best meshing efficiency occurs at 800–1000 rpm of pinion. The meshing efficiencies of these three design cases are almost same, and their differences are less than 0.5%. Considering the root strength of pinion, Cases II and III are better than Case I.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".