The Effect of Viscosity Ratio on the Hydrodynamics of Separation From an Oil-Coated Particle
Bibliographic record
Abstract
Separating oil from solid particles is of great importance in many industrial processes including the extraction of bitumen from oil sands, and the remediation of oil spills. The usual approach is to separate the oil from the solid by introducing another liquid (e.g. water). Separation is often assisted by fluid mixing, and chemical addition. Yet while oil-water-particle separation has been well studied from a chemical standpoint, little research has taken into account the effect of hydrodynamics on separation. In this work, the separation of oil from a single oil-coated spherical particle falling through an aqueous solution was evaluated as a function of viscosity ratio. Solvents were used to modify the viscosity of the oil. The experiments were recorded using a high-speed camera and post-processed using the MATLAB image-processing toolbox. A CFD model has also been developed to study this phenomenon. The results indicate that when viscous forces are strong enough, the oil film deforms, flows to the back of the sphere, and forms a tail that eventually breaks up into a series of droplets due to a capillary wave instability. When the viscosity ratio is small (i.e. the oil is less viscous than the solution), a thin tail forms quickly, the growth rate of the instability is high, and hence the tail breaks very quickly into smaller droplets. When the viscosity ratio is high (i.e. the oil is more viscous), more time is required for the deformation/separation to initiate, and the tail is thicker and breaks more slowly into larger droplets. It was observed that when the viscosity ratio is close to 1, the rate of separation is increased and maximum separation is achieved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".