2D‐ <scp>MHD</scp> Brinkman flow around circular cylinders inside a microchannel exhibiting wall roughness
Bibliographic record
Abstract
Abstract This investigation focuses on the dynamic behaviour of the steady, pressure‐driven flow of a two‐dimensional viscous incompressible fluid around circular cylinders of equal diameter within a rectangular permeable microchannel featuring wall roughness. The wall roughness is modelled by implementing Navier's slip condition on the horizontal channel walls with a phase difference, examining both small and large‐patterned wall roughness scenarios. The flow, characterized by a low Reynolds number, is subjected to an inclined magnetic field, while the induced magnetic field effects are neglected under a low magnetic Reynolds number assumption. The Brinkman equations describing the flow are solved using the boundary element method (BEM) based on stream function and vorticity variables. The results indicate that increasing Darcy numbers enhances the permeability of the porous medium, reducing flow resistance, particularly away from the channel walls. The Lorentz force maximizes drag when perpendicular to the flow and becomes less effective as the magnetic field inclination increases. Shear stress is minimized at Navier's slip and no‐slip conditions interface. This investigation supports advancements in targeted drug delivery in microfluidic applications, optimization of lab‐on‐chip devices for diagnostics, and improvement of fluid dynamics in heat exchangers and filtration systems.
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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".