Numerical Simulation of Taylor Flow in the Entrance Region ofMicrochannels
Bibliographic record
Abstract
Computational Fluid Dynamics (CFD) has been widely employed by investigators to simulate Taylor flow in microchannels. High-resolution images captured by numerical techniques reveal significant details of an ultra-thin liquid film around the gas bubble. The interface between the liquid and the gas phases is a decisive factor in order to determine the flow pattern, the gas bubble profile, the bubble length-separation distance, the slug length, and so forth. Since the thickness of the liquid film is on the order of 10-15 m for low capillary number flows, the mesh generation requires careful modeling to capture it and transport phenomena, such as momentum and heat. The present study is to develop a model of a transient Taylor flow in a two-dimensional microchannel using commercial ANSYS Fluent software. The Volume of Fluid (VoF) method was employed to simulate the interface between two phases, i.e., air and water. A comprehensive grid study was carried out to identify a sufficiently fine mesh to capture the film layer around the gas bubble in the uniform film thickness region. The curvatures of the nose and the tail of the gas bubbles were studied during traveling through the channel. Variations of the lengths of slugs and plugs were also measured as the functions of time. The numerical results were validated by available correlations of liquid film thickness, and slug length in previous studies.
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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) | 0.000 | 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 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".