Particle Removal From Sandbed Deposits in Horizontal Annuli Using Viscoelastic Fluids
Bibliographic record
Abstract
Summary This paper presents results of an experimental study on how fluid viscoelastic properties would influence the particle removal from the sandbed deposited in horizontal annuli. Water and two different viscoelastic fluids were used for bed-erosion experiments. The particle-image-velocimetry (PIV) technique was used to measure the local fluid velocity at the fluid/sandbed interface, allowing for accurate estimation of the fluid-drag forces and the turbulence stresses. It was found that polymer fluids needed to exert higher level drag forces (than those of water) on the sandbed to start movement of the particles. Results have also shown that, at the critical flow rate of bed erosion, the polymer fluids yielded higher local fluid velocities and turbulent stresses than those of water. Moreover, the local velocity measurements by means of the PIV technique and the resultant bed-shear-stress calculations indicated that enhancing polymer concentration under the constant flow rate should also enhance the drag forces acting on the sandbed. However, these improved fluid hydrodynamic forces did not result in any improvement in the bed erosion. Therefore, the mechanism causing the delay in the bed erosion by polymer additives could not be explained by any decrease in the local fluid velocity and the turbulence. The primary reason for the delayed bed erosion by the polymer fluids was suggested to be linked to their viscoelastic properties. Two possible mechanisms arising from the elastic properties of the polymer fluids that hinder bed erosion were further discussed in the paper. The stress tensor of the viscoelastic-fluid flow was analyzed to determine the normal stress differences and the resultant normal fluid force acting on the particles at the fluid/sandbed interface. The normal force induced by the normal stress differences of the viscoelastic fluid was identified as one of the possible causes of the delayed bed erosion by these types of fluids.
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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) | 0.001 | 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".