An Imaging Technique For Characterizing Viscoelasticity Of Drag-Reducing Solutions
Bibliographic record
Abstract
Existing rheometric measurement techniques that use load and displacement sensors are unable to resolve the non-Newtonian features of dilute drag-reducing solutions. In the present investigation back-lit particle image velocimetry, or particle shadow velocimetry, was used to quantify the complex dynamics of these fluids in a novel flow geometry. The flow of three non-Newtonian solutions were investigated in a periodically constricted tube (PCT). The radius of the tube walls was sinusoidal with respect to the streamwise direction. The three fluids under consideration were aqueous solutions of a flexible polymer, rigid polymer and surfactant, all of which were previously shown to instill drag reduction in a high Reynolds number, turbulent channel flow. Three solutions with mass concentrations of 0.01%, 0.03% and 0.05% were considered for each additive. Steady shear viscosity measurements demonstrated that all rigid and flexible polymer solutions were noticeably shear-thinning, while the surfactant solutions had a water-like shear viscosity. Each solution was measured at five Reynolds numbers between approximately 1 and 100 within the PCT. Relative to Newtonian fluids within the PCT, the rigid polymer solutions produced a plug-like flow with a blunted velocity and attenuated vorticity at radial coordinate further from the tube centerline. The flexible polymer solution, known to have appreciable amounts of elasticity, demonstrated a distinct chevron shaped velocity contour, coupled with a negative vorticity pattern within the contraction regions of the PCT. Despite having a seemingly Newtonian shear viscosity, the surfactant solutions produced velocity and vorticity patterns reminiscent of the flexible polymer. The general implication is that surfactants share similar elastic traits as flexible polymers. The vorticity transport equation was used to derive distributions of the non-Newtonian torque, more commonly called the `polymer torque' in other literature. It was revealed that the non-Newtonian torque was the source of vorticity field disruption in the flows of flexible polymer and surfactant solutions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".