Hydrodynamic dispersion in steady buoyancy‐driven geological flows
Bibliographic record
Abstract
An analytical model is developed to evaluate mixing induced by natural convection in a fluid‐saturated porous medium. First, the velocity and concentration fields are decoupled to generate a steady state velocity field and initiate a naturally convective system. In order to decouple the velocity and concentration fields, a steady thermal natural convection is established by imposing a destabilizing vertical temperature gradient across a porous layer and then introducing a passive tracer into the system. Based on the steady velocity field, effective longitudinal and transverse dispersion coefficients are evaluated using the shear flow dispersion theory, and convective mixing of the passive tracer is obtained using the developed analytical mixing model. The estimated dispersion coefficients and convective mixing are then characterized by the system Rayleigh and Sherwood numbers. The mixing obtained by the analytical model is then compared with high‐resolution numerical simulations. The results reveal that the simple analytical solution represents the nonlinear mixing involved in such a system and agrees with the numerical results. The developed model has potential applications in geophysical and geothermal buoyancy‐driven flows.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".