Numerical investigation of three-dimensional hybrid Cu–Al<sub>2</sub>O<sub>3</sub>/water nanofluid flow over a stretching sheet with effecting Lorentz force subject to Newtonian heating
Bibliographic record
Abstract
This work compares the heat transfer characteristics of traditional nanofluid with that of emerging hybrid nanofluid. Hybrid nanofluid, a new type of conventional fluid, has been used toward the enhancement of heat transfer in the boundary layer flow. A new model of thermophysical properties is employed to investigate the effects of Lorentz force over a three-dimensional stretching surface subject to Newtonian heating. Comparisons are obtained through the numerical parametric study, which has been carried out to explore the effects of various physical parameters involved in the problem. From this study it is observed that the heat transfer rate of hybrid nanofluid (Cu–Al2O3/water) is higher than nanofluid (Cu/water) even in the presence of a magnetic field environment. By opting to use different and appropriate nanoparticle proportions in hybrid nanofluid, the desired heat transfer rate can be achieved.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".