TWO-PHASE FRICTION FACTOR IN GAS-LIQUID PIPE FLOW
Bibliographic record
Abstract
An improved friction factor prediction model for two-phase gas-liquid pipe flow is proposed. The model is based on a previous no-slip formulation where a mixture Reynolds number was defined. In this study, the mixture Reynolds number is modified by introducing slip-ratio information through the inclusion of void-fraction and flow-pattern dependent models. An experimental database reconstituted from the available literature and new frictional pressure-drop data for air-water horizontal flow in an I.D. 0.0204m pipe are also presented. The full database considers several different flow conditions for horizontal two-phase flow of refrigerants and air-water mixtures. It was compared to predictions of models from the literature as well as the new proposed model. We found that the proposed and Müller-Steinhagen-and-Heck methods provide better agreement for the current experimental database. It is shown that the inclusion of void-fraction information on the previous mixture Reynolds definition improves the friction-factor prediction
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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 | 0.000 | 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 | 0.000 |
| 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".