Experimental Investigation on Pressure Drop In Liquid-Liquid Taylor Flow Regimes
Bibliographic record
Abstract
This study presents an experimental investigation on pressure drop in liquid-liquid Taylor flow regimes with the objective of extending previous research carried out on this topic.Pressure drop measurements were obtained over a wide range of Capillary (2.9 × 10 -4 ≤ 𝐶𝐶𝐶𝐶 ≤ 5.1 × 10 -2 ) and Reynolds (0.17 ≤ 𝑅𝑅𝑅𝑅 ≤ 45) numbers while carrier to dispersed viscosity ratio (𝜇𝜇 * ) spanned from 0.059 to 23.2.Five different liquid-liquid flow combinations were examined within capillaries of diameter 0.8𝑚𝑚𝑚𝑚.Analysis of existing models from relevant literature reveals that they are limited to specific ranges of Reynolds and Capillary numbers and not sufficiently accurate to predict pressure drop values over a wide range of viscosity ratios.Through comparison with experimental data from this study, the strengths and weaknesses of these models are identified and a more fundamental understanding of predicting pressure drop in Taylor flow regimes is developed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".