Experimental and Numerical Analysis of Heat Transfer and Flow Phenomena in Taylor Flow Through a Straight Mini-Channel
Bibliographic record
Abstract
Abstract This study experimentally and numerically investigates the hydrodynamic characteristics and heat transfer of developing and fully developed laminar liquid–liquid Taylor flows. The problem is conducted in circular mini-channels with different diameters subjected to a constant wall temperature boundary condition. An experimental setup is designed employing an open-loop water/oil two-phase nonboiling flow at mini-scale tubing sizes of 1.42, 1.52, and 1.65 mm. Two silicone oils with the dynamic viscosities of 1 and 5 cSt at several volumetric flow rates are used to establish segmented flow. The impacts of the channel diameter, viscosity, and flow rate ratio on the flow pattern, pressure drop, film thickness, and heat transfer rate are discussed. In good agreement with the literature, it is found that the pressure drop generated by the interface increases the total pressure loss by up to 200% compared to the single-phase flow. The results also explain how recirculating regions within the slugs influence the film region and the physics of backflow. Furthermore, introducing segmented water slugs significantly enhances the heat transfer rate as the dimensionless thermal length decreases. A significant relation between the recirculating regions and heat transfer has been demonstrated for the first time.
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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 | 0.001 |
| 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) | 0.002 | 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".