Study of oil‐soluble and water‐soluble drag reducing polymers in multiphase flows
Bibliographic record
Abstract
Abstract Multiphase flow industrial applications require reduced frictional pressure drop (drag) and lower operating costs. Drag reducing polymers (DRPs), which do not require additional infrastructure, meet this requirement. Therefore, this study investigated the effects of water‐soluble polar ZETAG® 8165 and nonpolar oil‐soluble polyisobutylene (PIB) DRPs on pressure gradient and percentage drag reduction using two‐phase air‐water and air‐oil flows, and three‐phase air‐oil‐water flow. The conduit comprised a 22.5 mm I.D. and 2.48 m long horizontal pipe. The fluid flow pattern and DRP shear stability were also studied. The functional mechanism of DRP, not adequately addressed in the literature, was especially revisited. This work suggests that the resultant interaction between the DRP state and the external environment dictates its ability for dampening turbulent eddies, streamlining the velocity field, and eventually increasing the thickness of the laminar sublayer. The DRP state includes its chemical structure and hydrodynamic size. On the other hand, the external environment comprises fluid flow pattern, polarity, phase morphology, and intensity of turbulence. Hence, the functional mode of a DRP is more involved than what the literature usually reports. ZETAG® 8165, having longer branches and ion‐pairs around the backbone, showed less shear degradation than the fairly straight‐chain PIB. The effects of these structural differences were also well‐reflected in their varying abilities to transpose flow pattern, and reduce drag and pressure gradient. For a given DRP, the air flow rate promoted or demoted the DRP performance, depending on the experimental design.
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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 | 0.000 | 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 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".