Characteristics of Two-Phase Flows in a Rectangular Microchannel with a T-Junction Type Gas-Liquid Mixer
Bibliographic record
Abstract
In this study, gas–liquid two-phase flows in a horizontal rectangular microchannel have been investigated. The rectangular microchannel has a hydraulic diameter of 0.235 mm, and a width and depth of 0.24 mm and 0.23 mm, respectively. A T-junction-type gas–liquid mixer was used to introduce gas and liquid in the channel. In order to know the effects of liquid properties, distilled water, ethanol, and HFE7200 were used as the test liquids, with nitrogen gas was used as the test gas. The flow pattern, the bubble length, the liquid slug length, and the bubble velocity in two-phase flow were measured with a high-speed video camera, and the void fraction was determined from the bubble velocity data and the superficial gas velocity data. In addition, the pressure drop was also measured with a calibrated differential pressure transducer. The bubble length data were compared with the calculation by the scaling law proposed by Garstecki et al. [7]. The bubble velocity data and/or the void fraction data were well correlated with the well-known drift flux model [12] with a new distribution parameter correlation developed in this study. The frictional pressure drop data were also well correlated with the Lockhart-Martinelli method with a correlation of the two-phase friction multiplier.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".