Pressure drop of slug flow in microchannels with increasing void fraction: experiment and modeling
Bibliographic record
Abstract
Pressure drop in a gas-liquid slug flow through a long microchannel of rectangular cross-section was investigated. Pressure measurements in a lengthy (∼0.8 m) microchannel determined the pressure gradient to be constant in a flow where gas bubbles progressively expanded and the flow velocity increased due to a significant pressure drop. Most of the earlier studies of slug flow in microchannels considered systems where the expansion of the gas bubbles was negligible in the channel. In contrast, we investigated systems where the volume of the gas phase increased significantly due to a large pressure drop (up to 1811 kPa) along the channel. This expansion of the gas phase led to a significant increase in the void fraction, causing considerable flow acceleration. The pressure drop in the microchannel was studied for three gas-liquid systems; water-nitrogen, dodecane-nitrogen, and pentadecane-nitrogen. Inside the microchannel, local pressure was measured using a series of embedded membranes acting as pressure sensors. Our investigation of the pressure drop showed a linear trend over a wide range of void fractions and flow conditions in the two-phase flow. The lengths and the velocities of the liquid slugs and the gas bubbles were also studied along the microchannel by employing a video imaging technique. Furthermore, a model describing the gas-liquid slug flow in a long microchannel was developed to calculate the pressure drop under conditions similar to the experiments. An excellent agreement between the developed model and the experimental data was obtained.
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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".