Investigation on dip coating process by mathematical modeling of non-Newtonian fluid coating on cylindrical substrate
Bibliographic record
Abstract
A mathematical model for the dip coating process has been developed for cylindrical geometries with non-Newtonian fluids. This investigation explores the effects of the substrate radius and hydrodynamic behavior of the non-Newtonian viscous fluid on the resulting thin film on the substrate. The coating fluid studied, Dymax 1186-MT, is a resin for fiber optics and used as a matrix to suspend 1 vol. % titanium dioxide particles. The coating substrate is a 100 μm diameter fiber optic diffuser. Ellis viscosity model is applied as a non-Newtonian viscous model for coating thickness prediction, including the influence of viscosity in low shear rates that occurs near the surface of the withdrawal film. In addition, the results of the Newtonian and power law models are compared with the Ellis model outcomes. The rheological properties and surface tension of fluids were analyzed and applied in the models and a good agreement between experimental and analytical solutions was obtained for Ellis model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".