Dynamic control of droplets and pockets formation in homogeneous porous media immiscible displacements
Bibliographic record
Abstract
Interfacial instabilities of immiscible two-phase radial flow displacements in homogeneous porous media are analyzed for constant and time-dependent sinusoidal cyclic injection schemes. The analysis is carried out through numerical simulations based on the immersed interface and level set methods. The effects of the fluid properties and the injection flow parameters, namely, the period and the amplitude, on the formation of droplets and pockets are analyzed. It was found that larger capillary numbers or smaller viscosity ratios lead to more droplets/pockets that tend to appear earlier in time. Furthermore, the period and amplitude of the cyclic schemes were found to have a strong effect on droplets/pockets formations, and depending on their values, these can be enhanced or attenuated. In particular, the results revealed that there is a critical amplitude above which droplets and pockets formation is suppressed up to a specified time. This critical amplitude depends on the fluid properties, namely, the viscosity ratio and surface tension as well as on the period of the time-dependent scheme. The results of this study indicate that it is possible to use time-dependent cyclic schemes to control the formation and development of droplets/pockets in the flow and in particular to delay their appearance through an appropriate combination of the displacement scheme’s amplitude and period.
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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) | 0.000 | 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 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".