Evaluation of Time-Varying Mesh Stiffness of Gears with Tooth Spalls Modeled as Spherical Shapes
Bibliographic record
Abstract
The analysis of the vibration behavior of a gear transmission under healthy and damaged tooth conditions by dynamic simulation requires accurate knowledge of the gear Time Varying Mesh Stiffness (TVMS) and its corresponding changes when a tooth fault occurs. Common methods for evaluating the TVMS under conditions of tooth spall utilize specific geometric shapes to model the spalling defects. These methods generally assume that the tooth spall has a flat bottom with cliff-like material loss i.e. a suddenly changing dent depth. However, in practice, the flake of the surface material usually possesses a curve shaped bottom with a gradually changing dent depth. Therefore, modeling the tooth spall as a flat bottom with constant dent depth may not actually reflect the tooth spall features in practice. To address this shortcoming, this paper proposes a method that uses a spherical shape profile to model gear tooth spalling. The effectiveness of the proposed method in modeling gear TVMS under single and multiple tooth spalling conditions is then analyzed.
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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) | 0.001 | 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".