Natural Convection in an Annular Enclosure: Influence of Magnetic Field-dependent Thermal Conductivity on Heat Transfer
Bibliographic record
Abstract
In this paper, the natural convection heat transfer characteristics are investigated inside an annular enclosure containing Magnetic Nanofluid (MNF) (i.e., Fe3O4 nanoparticles are dispersed in Kerosene). A uniform magnetic field (H) is applied along the axial direction of the enclosure. Magnetic field-dependant thermal conductivity (k) of the MNF is considered as a nonlinear function which is interpolated from the experimental results. Finite element method is utilized to solve the governing equations for various magnetic field strengths, volume fractions of MNF, and Rayleigh numbers. Average Nusselt numbers along the hot wall are calculated and compared for different scenarios. The results show that the applied magnetic field has a significant effect on the heat transfer rate, more specifically on the Nusselt number, in the enclosure for higher volume fractions of nanoparticles. Thermal conductivity enhancement as a result of using magnetic field can be used for various applications such as thermal energy storage in which the heat transfer needs to be accurately controlled.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".