Droplet Impact and Penetration onto Structured Pore Network Geometries
Bibliographic record
Abstract
The impact of the water droplet on permeable substrate has been studied experimentally and numerically. Reynolds number (Re) and Weber number (We) are found to be the governing non- dimensional numbers. Porosity of the substrate is the geometry parameter studied in this thesis. Impact and penetration of the water droplet has been studied experimentally on structured parallel holes on a solid substrate to track penetration in the presence of capillarity. Liquid penetration into the holes was initially rapid, driven by the inertia of the impacting liquid and then much slower, caused by capillary forces that drew in the liquid. The rate of liquid movement was predicted by a simple model that included liquid pressure, surface tension and viscous effects. The\narea of liquid, solid contact inside the holes was significant, varying from 5% to 30% of the total droplet-substrate contact area as droplet height was raised from 1 cm to 5 cm. The enhanced contact area increased the surface energy of the droplet and reduced the energy available for droplet recoil.\nPhysics of capillary penetration in our experimental studies extended our research to model droplet impact and penetration into structured permeable geometries using ANSYS-FLUENT 14.0. The significant objective of the numerical studies is characterization of the ratio of penetrated volume rather than droplet initial volume. Porosity of the substrate has been studied to evaluate the effect of this value in penetration regime. Investigating the effect of impact inertia achieved by changing Re number from 50 to 2000 and penetrated volume showed that increasing Re number increases liquid penetrated into the pore network. Spreading diameter and droplet height showed similar oscillatory behaviors, but larger degree in height rather than spreading diameter. In the end, dynamic of bubble formation at range of Re has been observed. Small bubbles start forming at Re = 200. By increasing Re to 500 entrapped bubbles into the pore network starts to disappear due to the larger degree of momentum of the impact which pushes the bubbles closer to the liquid/gas interface. For Re > 1000, formation of bubbles changes from spherical small form to large slug form.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".