Rayleigh–Taylor mixing in porous media at an extreme viscosity contrast
Bibliographic record
Abstract
We present experimental findings of Rayleigh–Taylor (RT) instability within porous materials, with a significant viscosity contrast of M ≈ 106, where M represents the ratio of the dynamic viscosity of heavy fluid to that of light fluid, M = μH/μL, and Ra = 6.62 × 104–6.67 × 105, and Rayleigh number (Ra) quantifies the relative significance of buoyancy forces compared to viscous forces. We observe that the lighter fluid diffuses into the denser one, creating a transient diffusive boundary layer that rapidly becomes unstable, transitioning into a convection-dominated regime. Initially, the instability manifests as small fingers protruding upward. However, these fingers coalesce and form fewer major fingers. Convection persists until fingers reach the upper boundary, transitioning into a shutdown regime. During the convection-dominated phase, the extracted solute concentration exhibits a linear relationship with time on a log –log scale, suggesting a constant mass flux. However, this flux diminishes upon entering the shutdown regime. The steady flux, quantified by the Sherwood number, correlates with the Rayleigh number as Sh = 0.046Ra, indicating independence from the height of the porous medium. We have also developed a simple conceptual model that effectively captures the dynamics of RT mixing.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".