On the Dynamics of Two‐Component Convective Dissolution in Porous Media
Bibliographic record
Abstract
Abstract We studied the influence of the diffusion contrast between species on the dynamics of Rayleigh‐Bénard (RB) convection in porous media. The onset time of buoyancy‐driven instabilities and convective dissolution flux was quantified using linear stability analysis and direct numerical simulations. The parametric analysis indicates eight distinct instability regions. Different stability mechanisms were characterized over the given range of diffusivity and relative buoyancy ratios. In particular, transition from instabilities solely by double diffusion to RB convection was identified using linear stability analysis and confirmed using nonlinear simulations. The parametric analysis on the onset also indicates that double diffusion has a potential to accelerate or slow down the RB convection depending on the solutes diffusion contrast. This study provides new insight into the effect of diffusion contrast and can be used to develop strategies for acceleration and deceleration of buoyancy‐driven instabilities.
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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".