Helical Gears, Effects of Tooth Deviations and Tooth Modifications on Load Sharing and Fillet Stresses
Bibliographic record
Abstract
Based on a few specific cases, this paper presents a comparative investigation of the effect of helix slope and form deviation tolerances as specified by grades 5 and 7 of the ANSI/AGMA ISO 1328-1 Standard for Cylindrical Gears. In addition, the consequences of longitudinal flank crowning and radial tip relief modifications are investigated, as applied on a misaligned helical gear set. For all simulations, the express model (Guilbault et al., 2005, ASME J. Mech. Des., 127(6), pp. 1161–1172) is employed. The bending deflection and fillet stresses are obtained from a combination of finite strip and finite difference meshes. The rolling-sliding motion of mating gear teeth is modeled with a cell discretization of the contact area, which offers fast and accurate results. Similar contact conditions arise from a helix slope deviation or a misalignment of the gear set: the first contact point is driven to a theoretical contact line endpoint. Such a condition produces a localized, and clearly impaired, contact area subject to overloading. Consequently, flank crowning and tip relief corrections must be carefully regarded in the design process. The presented results highlight that, if improperly combined, profile modifications can amplify the overloading condition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".