An improved method for applying the lockhart–martinelli correlation to three‐phase gas–liquid–solid horizontal pipeline flows
Bibliographic record
Abstract
Abstract Three‐phase (G/L/S) horizontal pipe flow data collected from the literature are used to evaluate the performance of a number of correlations designed to predict the pipeline pressure gradient. In the present study, a number of popular two‐phase gas–liquid pressure loss correlations were modified for three‐phase flow predictions. The primary modification is to assume that the slurry (L/S) mixture behaves as a singlephase. The modified Dukler and the Beggs and Brill correlations did not provide accurate estimates of the three‐phase pressure gradients. When the classical Lockhart–Martinelli (L–M) correlation was used, along with a kinematic friction loss model to calculate the slurry (L/S) superficial flow pressure gradient, accurate predictions of the three‐phase (G/L/S) pressure gradient were obtained provided the slurry did not exhibit non‐Newtonian behaviour and that Coulombic (sliding bed) friction was negligible. Additional experiments should be conducted before the improved version of the L–M correlation is applied to commercial installations with pipe diameters greater than 100 mm.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".