Drainage under Nonequilibrium Conditions: Exploring Wettability and Dynamic Contact Angle Effects Using Bundle‐Of‐Tubes Simulations
Bibliographic record
Abstract
Numerical simulators often assume that equilibrium capillary pressure–saturation conditions are maintained as changes in fluid saturation are taking place; however, equilibrium conditions may not be maintained in all circumstances. An alternative approach is to describe a nonequilibrium difference between wetting and nonwetting fluid pressures as a function of the rate of change of saturation and a damping coefficient. It has been proposed that this damping coefficient may be a function of multiple fluid and porous medium properties, including wettability. This study used bundle‐of‐tubes simulations to provide insight into the potential effect of increasing equilibrium contact angle, as a measure of wettability, on the magnitude of the damping coefficient. The effect of considering the dynamic contact angle, as a function of wettability, was also investigated. Results showed that when dynamic contact angles were considered, larger damping coefficient values were predicted. These values varied nonmonotonically with equilibrium contact angle and had maximum values near an equilibrium contact angle of 60°. The results also showed that values of the damping coefficient were dependent on the type of pressure boundary condition used. A steadily increasing boundary pressure resulted in larger damping coefficient values that were a function of the equilibrium contact angle, and better represented experimental pressure–saturation observations, than simulations using a series of instantaneous steps. These results suggest that assuming equilibrium conditions may be reasonable under wettability conditions characterized by equilibrium contact angles near 90°, potentially for contact angles near 0°, but not at moderate equilibrium contact angles. Further work is necessary, however, to determine the underlying physical mechanisms that govern nonequilibrium pressure differences and the magnitude of the damping coefficient.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".