Meshing performance of spiral bevel gear with different loads and modules considering edge contact by finite element method
Bibliographic record
Abstract
To analyze the edge contact of spiral bevel gears, owing to its effect on meshing performance, batch processing is performed based on a static solver and the finite element method (FEM) because of its computational speed advantage. A series of programs automatically perform the functions of modeling, analysis, and extraction of performance indexes. Starting from the entrance meshing position to the exit meshing position, a series of models was built and analyzed to describe the whole meshing process of the gear pair. For a specific gear pair, contact and bending stresses, contact stress patterns, loaded transmission errors, contact forces, and load sharing coefficients are calculated under five different load conditions and the change rules are summarized. Edge contact phenomenon occurs as the load increases to a critical value, resulting in a sharp increase in contact stress. As the load increases, the load sharing coefficient decreases gradually and the absolute value of transmission error increases, but the fluctuation of transmission error first decreases and then increases. In addition, the effect of modules is discussed and the results show that large modulus will decrease stress, contact ratio, and edge contact, but there is a certain module to minimize the fluctuation of transmission error.
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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 | 0.000 |
| 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".