The Soret effect on convection in a horizontal porous domain under cross temperature and concentration gradients
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Bibliographic record
Abstract
Natural convection with Soret effect in a binary fluid saturating a shallow horizontal porous layer is studied both numerically and analytically. The vertical walls of the enclosure are heated and cooled by uniform heat fluxes and a solutal gradient is imposed vertically. In the formulation of the problem, we use the Darcy model and the density variation is taken into account by the Boussinesq approximation. The governing parameters of the problem are the aspect ratio, A , the thermal Rayleigh number, R T , the buoyancy ratio, N, the Lewis number, Le and the Soret coefficient, N S . The analytical solution, based on the parallel flow approximation, is found to be in good agreement with a numerical solution of the full governing equations. In the presence of a vertical destabilizing concentration gradient, the existence of both natural and antinatural flows is demonstrated. When the vertical concentration gradient is stabilizing, multiple steady state solutions are possible in a range of buoyancy ratio, N, that depends strongly on the Soret coefficient, N S .
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| 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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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