Natural Convection in an Enclosure: Effect of Magnetic Field Dependent Thermal Conductivity
Bibliographic record
Abstract
In this paper, the natural convection heat transfer process is investigated inside an annular enclosure filled with a magnetic nanofluid (Fe 3 O 4 magnetic nanoparticles dispersed in Kerosene).A uniform magnetic field (H) is applied along the axial direction of the enclosure.Thermal conductivity (k) is considered as a function of magnetic field.A nonlinear relationship between magnetic field and thermal conductivity in the magnetic nanofluid (MNF) is assumed and interpolated.Finite element method is utilized to solve the governing equations and calculate the Nusselt number and it is presented as a function of volume fraction and magnetic field strength.The results show the significant effect of applied magnetic field on heat transfer rate, more specifically on Nu, in the enclosure when higher volume fractions of nanoparticles are used.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 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".