Modeling and Prediction of Mechanical Behavior of Plastic Gears in Simulated Wear Situation
Bibliographic record
Abstract
The present work shapes a normal plastic gear and simulates the corresponding worn one in order to predict its mechanical behavior in operation depending on the wear. To predict the mechanical behavior of plastic gears, a modeling of the gears has been done under SOLIDWORKS. Then with ALGOR, which uses the FEM, we studied two types of gear. A normal tooth of each type of gear has been net as well as the corresponding worn tooth. We opted for the study of two cases of charge. The first (case 1) corresponds to the application of strength to the head of the tooth (Fig. 2) and the second (case2) at the pitch point of the tooth (Fig. 3). We noticed the stresses and deformations on the nodes located on the right profile of the tooth, the first node is taken at the head of the tooth. The wear has been assumed uniform on the right profile from the head to the root. The tooth has been assumed embedded at the root. We obtained some results which could allow the prediction of the number of revolutions to breaking off, knowing the wear according to this cycle.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".