Heat Transfer in Liquid–Liquid Taylor Flow in Miniscale Curved Tubing for Constant Wall Temperature
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Bibliographic record
Abstract
In this paper, heat transfer enhancement using liquid–liquid Taylor flow in miniscale curved tubing for isothermal boundary conditions is examined. Copper tubing with an inner tube diameter of D = 1.65 mm and different radii of curvature and lengths is used in the experiments. Taylor flow is created using water and low-viscosity silicone oils (0.65 cS, 1 cS, and 3 cS) to examine the effect of Prandtl number on heat transfer rates in curved tubing. A series of experiments are conducted using tubing with constant length and variable curvature as well as variable length and constant curvature. The experimental results are compared with models for liquid–liquid Taylor flow in straight tubing and single-phase flow in curved tubes. The results of the research highlight the effects of liquid–liquid Taylor flow in curved tubing. This research provides new insights into the effect of curvature on heat transfer enhancement for liquid–liquid Taylor flow in miniscale curved tubing, at a constant wall temperature.
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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 | 0.001 | 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 | 0.001 |
| 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 it