Two-Phase Flow Regime Transitions in Microchannels: A Comparative Experimental Study
Bibliographic record
Abstract
In recent years, micro-technologies have become very important to cutting edge industries such as aerospace and biotechnology. In the fluidic research area, two-phase flow study in microchannels has been an emerging topic in the past few years. Characteristics of two-phase flow in microchannels such as flow regimes, pressure drop, void fraction, and heat transfer are now being extensively studied by numerous groups. The ultimate goal of this research ranges from compact heat exchangers to small-sized refrigeration systems. One of the major drawbacks in this area to date is the lack of a universal flow regime map enabling the prediction of flow regimes in microchannels. In the present study, a new test rig was designed and constructed to extend the range of the existing data on flow regimes. Several flow regime maps, for a hydraulic diameter of less than 1.0 mm obtained from a comprehensive literature review, are tested and compared. A total of approximately 1475 experimental data points from present and previous studies performed in channels with Dh ≤ 1.0 mm were used for comparison. Two universal flow regime maps were created, one each for horizontal and vertical channels with a hydraulic diameter ranging between 0.1 mm and 1.0 mm. The resulting universal maps presented here are based on flow regimes observed in all the studies on two-phase flow in microchannels. We suggest that the use of these flow regimes could help diminish the amount of discord present among research groups pertaining to the definition of flow regimes. Based on the comparisons between the universal maps and different experimental flow regime maps, appropriate conclusions on the effects of channel orientation and geometry are suggested.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".