Computational study of Newtonian laminar annular horizontal displacement flows with rotating inner cylinder
Bibliographic record
Abstract
We computationally study the effects of inner cylinder rotation on the laminar displacement flow of two Newtonian fluids along a horizontal eccentric annulus. This flow arises in primary cementing operations in the oil and gas industry, used to seal wells and prevent leakage. We investigate how the rotational motion of the inner cylinder influences the displacement, affecting the interplay of viscosity and density differences, as well as eccentricity. We first simulate a series of experiments recently performed, in order to validate the computational approach. We then study the effects of the rotating inner cylinder in more detail. The rotation shears the fluid in the narrow annular gap and also drags fluid around the annulus, typically resulting in helical streamlines and a spiral pattern of the concentration. Over short timescales, the rotation tends to increase dispersion, but the redistribution of the fluids around the annulus can then improve the overall displacement, i.e., reducing slumping effects due to buoyancy. We also observe a new patterning instability at the inner cylinder, which was not visible in the previous experiments. This instability arises from destabilization of the wall film of displaced fluid, which forms naturally on the walls of the annular gap. We have studied the dimensional parameter space where this instability occurs. Strong buoyancy can suppress the instability, and a threshold value of dimensionless rotation velocity is required for onset of the instability.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".