Numerical analysis of buoyancy-driven immiscible exchange flows in axially rotating pipes
Bibliographic record
Abstract
This numerical investigation examines buoyancy-driven immiscible exchange flows in near-horizontal rotating pipes using OpenFOAM simulations, with direct applications to primary cementing of oil and gas wells. The study analyzes a density-unstable configuration where a higher-density fluid (water solutions) overlies a lower-density fluid (silicone oil), focusing on three critical parameters: the pipe's rotational angular velocities, density differences between fluids, and inclination angles. Analysis reveals that the displacing front velocity is an increasing function of density differences and a decreasing function of inclination angles and rotations. Higher density differences, faster rotations, and steeper inclinations could all enhance the Kelvin-Helmholtz instability. Higher pipe rotation dampens axial velocity fluctuations while enhancing radial direction velocity fluctuations, whereas both increased density differences and decreased inclination angles intensify axial velocity fluctuations, with cross-sectional components remaining relatively unchanged across all conditions. Additionally, turbulent kinetic energy is enhanced by faster rotations, higher density differences, and steeper inclination angles. These findings characterize the complex interplay between rotation, density difference, and inclinations in immiscible exchange flows, and provide some insights into practical cementing operations through velocity fluctuation and turbulent kinetic energy analysis.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".