Mixed convection of electrically conducting and viscous fluid in a vertical channel using Robin boundary conditions
Bibliographic record
Abstract
An analytical and semi-analytical method is used to solve two-fluid magneto-hydrodynanamic flow and heat transfer in the presence of a constant electric field in a vertical channel using Robin boundary conditions. The channel is filled with electrically conducting fluid in one region and non-conducting fluid in the other region, which are immiscible. The viscous and Ohmic dissipation terms are included in the energy equation. The fluids in both regions are incompressible and the transport properties are assumed to be constant. Separate solutions are matched at the interface using suitable matching conditions. First, the simple cases of the negligible Brinkman number or the negligible Grashof number are solved analytically. Then, the combined effects of buoyancy forces and viscous dissipation are analyzed by a perturbation series method (PM) valid for small values of the perturbation parameter. To relax the conditions on the perturbation parameter, the flow fields are solved by using the differential transform method (DTM). The results are presented for various values of mixed convection parameter, perturbation parameter, Hartman number, viscosity ratio, width ratio, conductivity ratio, and Biot numbers for open and short circuits. The effects of these parameters on the physical characteristics, such as the Nusselt number at the walls, is also studied. The solutions obtained by DTM are justified by comparing the solutions obtained by PM, and good agreement is found.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".