Effect of Microchannel Curvature on Water Droplet Dynamics in a Highly Viscous Flow
Bibliographic record
Abstract
This work is dedicated to the three-dimensional (3D) computational fluid dynamics (CFD) simulations of the microchannel curvature effect on water droplet dynamics in a highly viscous flow. Dynamics of 10 μm water droplets in bitumen medium flowing through U-shaped tubes of square-cross-section and of h = 40 μm width is investigated. The channel curvature radius R varies from 0.25 h to 2 h and the inlet Reynolds number Re in from 2 to 10. The coupled level-set and volume of fluid (CLSVOF) methods are combined with the adaptive mesh refinement (AMR) technique to accurately simulate a droplet flow regime. Different geometry performances are compared using one-dimensional (1D) diagrams for integral flow characteristics and 3D visualization of the liquid–liquid interface. Flows in the vicinities of the convex and concave walls are found to control droplet deformation and breakup patterns. The results reveal that at Re in ≥ 7, the flow causes droplet breakup and temporary coalescence associated with the formation of long worm-shaped droplets. Differently positioned droplets for each Re in, bend radius, and interfacial tension cases are assessed individually. As a result, a droplet behavior map is developed based on local capillary and Reynolds numbers.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".