Laminar annular displacement flows with rotating inner cylinder in large annuli
Bibliographic record
Abstract
We present computational results from simulations of displacement flows in inclined and horizontal eccentric annuli, both with and without a rotating inner cylinder. The study is aimed at understanding flows in the industrial process of primary cementing of oil and gas wells. Following from Sotoudeh and Frigaard [“Computational study of Newtonian laminar annular horizontal displacement flows with rotating inner cylinder,” Phys. Fluids 36, 083113 (2024)], we explore larger-scale annuli and flows that are more inertial. These compare favorably with results from a series of displacement flows in a large laboratory experiment. This establishes the utility of the three-dimensional simulations as a tool for in depth understanding of the effects of inner cylinder (casing) rotation. We find that rotation affects the displacement effectiveness directly by adding an azimuthal Couette component to the flow. This moves (advects) the fluids around the annulus, particularly near the inner cylinder wall. For adverse viscosity ratios m, sufficient rotation appears to increase the displacement efficiency, but for large viscosity ratios it is found to sometimes reduce an already effective displacement. These results are all focused at lab-scale experimental annuli. Over the full length of a typical oil or gas well, the casing will rotate many more times during than in an experiment. Thus, our conclusions based on a single annular volume pumped may need modification.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".