Mixed Convection in Superposed Nanofluid and Porous Layers Inside Lid-Driven Square Cavity
Bibliographic record
Abstract
Mixed convection in a lid-driven composite square cavity is studied numerically. The cavity is composed of two layers; a Cu–water nanofluid layer superposed a porous layer. The porous layer is saturated with the same nanofluid. The left and right walls of the cavity are thermally insulated. The bottom wall which is in contact with the porous layer is isothermally heated and being lid to the left, while the top wall is isothermally cooled and being lid to the right. Cavity walls are impermeable except the interface between the porous layer and the nanofluid. Maxwell-Brinkman model is invoked for the momentum exchange within the porous layer. Equations govern the conservation of mass, momentum, and energy within the two layers were modeled and solved numerically using under successive relaxation (USR) up- wind finite difference scheme. Four pertinent parameters are studied; nanoparticles volume fraction φ (0.0 - 0.05), porous layer thickness Wp (0.1 - 0.9), Darcy number Da (10-7 – 10-1), and Richardson number Ri (0.01 - 10). The results have showed that the existence of the porous layer in a specified value can enhance the convective heat transfer when Ri ≥ 1, while an adverse action of nanoparticles is recorded when Da ≥ 10-4.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".