Bibliographic record
Abstract
Under elastohydrodynamic (EHL) conditions, the temperature in the contact zone determines the load resistance of the lubricant film. Therefore, an efficient assessment of the scuffing risks requires accurate contact temperature predictions. The work presented in this paper develops a simple and prompt temperature model exploitable within any thermal EHL modeling approach. The model incorporates a multilayer lubricant film representation for the heat equation solution. The developments also include an original heat repartition factor expression and a simple formula for handling intermediate values of the Peclet number. The rolling/sliding conditions in the inlet cause temperature rises that also affect the film resistance in the contact zone; this study proposes an inlet temperature rise equation. This formula offers temperature predictions in agreement with reference values. The contact zone temperature predictions for the line of contact problem under sliding/rolling conditions agree remarkably well with published numerical results; for the evaluations presenting the higher absolute difference, the correspondence remained over 94% and 95% for the maximum and mean temperatures, respectively. Both line and elliptical contact conditions were tested and compared to experimental data available in the literature. The analysis evidenced the precision of the estimates; thus attesting to the accuracy of the model under any contact conditions. Finally, the results indicate that, depending on the pressure and speed combination, the shearing zone may occupy around 30% of the film thickness.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".