On Simulation of the Natural Convection Heat Transfer Between Circular Cylinder and an Elliptical Enclosure Filled with Nanofluid [Part I: The Effect of MHD and Internal Heat Generation/Absorption]
Bibliographic record
Abstract
I demonstrated numerically the natural convective heat transfer between inner heated circular cylinder located within cooled elliptical enclosure filled with copper-water nanofluid with internal heat generation/absorption in the presence of horizontal magnetic field. The dimensionless governing equations are solved numerically using finite element scheme. The considered parameters of this study Rayleigh number (103<Ra<107), Hartmann number (0<Ha<60), nanofluid volume fraction (0<<0.06), heat generation/absorption (-10<q<+10) and the horizontal position of the inner circular cylinder (-0.2+0.2). The results show that increasing Rayleigh number and nanofluid volume fraction increases the fluid flow strength and heat transfer rate. While Hartmann number increasing leads to reduce the Nusselt number. It is obtained also, that absorption of heat augments the heat transfer. Finally, it is found that when the circular cylinder moves into the left side, a better heat transfer will be obtained while it is recommended to move the inner cylinder into right for better fluid flow strength
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".