An Approximate Method of Analysis for Laminar Heat Transfer in Liquid-Liquid Taylor Flows in Mini Scale Tubing
Bibliographic record
Abstract
Abstract Heat transfer analysis of liquid-liquid Taylor flow in previous studies almost never shows the effect of slug length on heat transfer. The homogenous or single-phase analysis is often the only method available to deal with flow of multi components. In the present study a new approach is developed to model the segmented liquid-liquid Taylor flow as two separated systems and presenting heat transfer enhancement for each component. The effect of internal circulation and boundary layer renewal within the two fluid components is clearly observed. An experimental setup was assembled using open loop system at mini scale size in which liquid-liquid Taylor flow is heated under a constant wall temperature. Three silicone oils of 1, 3, and 5 cSt were segmented using distilled water at three volume fractions 0.25, 0.5 and 0.75. Finally, heat transfer data of the dimensionless mean wall heat flux shows good agreement with a predictive model proposed in an earlier work by the second author. The results show an impact of the fluid cell dimensions on the rate of heat transfer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".