Experimental Investigation of the Flow Front Behind a Liquid-Air Interface for Capillary Flow
Bibliographic record
Abstract
An experimental system for understanding the flow field near the meniscus during the capillarity or under capillary action is developed. Capillary flow is one of the mechanisms for driving fluid in a microfluidic device. The literature highlights that a significant amount of work has been done on the theoretical understanding of the capillary transport in rectangular microchannels. However, these models for capillary flow neglect the flow behavior at the liquid-air interface, which may have a significant influence in terms of the velocity field and the transience of the penetration depth in the micro-capillary. The objective of the present study is to understand the flow development during the advancement of the meniscus. The aim is to elucidate the dynamics of the three phase contact line and other micro-scale effects during the capillarity. A μ-PIV technique has been used to study the flow development near the meniscus and the results are further refined using a hybrid μ-PIV/PTV technique. Effects of surface tension in the fully developed flow regime during the advancement of meniscus are studied in detail. Variations in the centreline velocity of the progression of the meniscus and temporal variations in the development of flow are identified as possible areas for departure from theory.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".