Mathematical Modelling of MHD Natural Convection in a Linearly Heated Porous Cavity
Bibliographic record
Abstract
A linear increase in thermal boundaries towards the bottom of the porous cavity is considered for numerical flow analysis on MHD natural convection. The two-dimensional square shaped cavity is filled with the Cu-water nanofluid. The dimensionless equations are considered to interpret the fluid and heat flow inside the cavity with respect to the desired boundaries. The governing equations are solved using the finite difference techniques. The relevant dimensionless parameters used in the present study are Rayleigh number, Darcy number, solid volume fraction of the nanoparticles and Hartmann number to obtain the flow fields. Heatline flows picturization techniques involved in the study analyze the heat flow inside the cavity. As the Rayleigh number and Darcy number increases, an increase in streamlines flow velocity and convection heat transfer is observed. Convective heat transfer is interrupted by increasing the applied magnetic field effects. An improvement in the heat transfer is noticed by increasing the solid volume fraction of the particles.
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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 | 0.000 |
| 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 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".