Three-dimensional lubrication flow of a Herschel-Bulkley fluid
Bibliographic record
Abstract
In this paper three-dimensional lubrication flow of grease is analysed numerically. The lubrication flow configuration is formed by two ellipsoid rollers. The load is assumed to be light enough for the lubrication mode to be purely hydrodynamic. The fluid behaviour is modelled using the Herschel–Bulkley model, and a two-dimensional modified Reynolds equation is derived. The numerical solutions are obtained by using a hybrid spectral/iterative technique and the Galerkin projection scheme. The effects of the material and geometrical parameters on pressure distribution are emphasized in the study. The investigation is conducted for a situation where the two ellipsoids are fully immersed in a grease lubricant. The effect of the geometry on the pressure distribution is determined by varying the ratio of the semi-axes and the minimum gap of the two rollers, respectively. The effect of the material parameters is examined by varying the power-law index and yield stress. It is found that the pressure distribution is strongly influenced by the shape of the rollers, the size of the minimum gap of the rollers and the rheological parameters. Copyright © 2005 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".