Impact of magnetohydrodynamics (MHD) on energy transmission through ferrofluid saturating porous medium contained in a lid-driven trapezoidal container with triangular notched heater configuration
Bibliographic record
Abstract
This article conveys numerical simulations for energy flow by mixed convection under the impact of magnetohydrodynamics (MHD) through ferrofluid saturating porous media contained in a trapezoidal enclosure having triangular notched heater at the bottom wall when the container’s top boundary is in motion with constant speed. The side and top walls of the container are assumed to be cold, the bottom wall is insulated, and the triangular notched heater supplies uniform heat to the fluid. Equations governing the flow are initially exposed to penalty scheme to eradicate pressure from momentum equations, and subsequently, the Galerkin weighted residual method is employed to compute the numerical solutions for velocity and temperature profiles. Computed solutions are expressed in form of graphs for streamline circulations, isotherms, and local and mean heat flow rates for suitable ranges of important physical parameters governing the flow, including the Darcy number (10−5 ≤ Da ≤ 10−3), Reynolds number (1 ≤ Re ≤ 10), Hartmann number (30 ≤ Ha ≤ 100), Prandtl number (0.062 ≤ Pr ≤ 10), concentration of solid ferroparticles (0.03 ≤ [Formula: see text] ≤ 0.15), and Grashof number (105 ≤ Gr ≤107). This investigation deduces that flow strength rises with escalation in the concentration of ferroparticles, as well as Darcy and Grashof numbers. The convection energy flow regime appears dominating for small Hartmann number and large Prandtl number. The mean energy flow rate is found to increase with increase in Darcy and Grashof numbers and it attenuates with escalation in the Hartmann number.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".