Natural Convection and Soret Effect in a Multi-Layered Liquid and Porous System
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Bibliographic record
Abstract
We investigated the onset of natural convection and thermodiffusion in an initially quiescent multi-layer system consisting of a porous layer sandwiched between two layers of a binary mixture, while the whole system is being heated from above. Two different water-alcohol mixtures were used with Soret coefficients of opposite sign. Then in similar situation a hydrocarbon mixture were investigated. It was found that when the Soret coefficient is negative, the lighter species migrates towards the colder surface while the denser species migrates towards the hotter surface. When the Soret coefficient is positive, the lighter species migrates towards the hotter surface while the denser species migrates towards the colder surface. Also, increasing the temperature difference leads to a greater separation of the mixture components because of the increase in the density gradient. In addition, increasing the porosity reduces the separation ratio due to the increased fluid mixing in the pores.
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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 | 0.000 | 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 | 0.001 |
| 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 it