Heat transfer analysis of magneto-Eyring–Powell fluid over a nonlinear stretching surface with multiple slip effects: Application of Roseland’s heat flux
Bibliographic record
Abstract
Non-Newtonian fluid model is intricate, nonlinear, and interesting to study because of the presence of rheological flow parameters and viscoelastic properties, which tend to emerge and make industrial flows considerably more complex to explain accurately. Improvement of industrial applications, such as glass fabrication, is an important consequence of this study. In this manuscript, we have explored the combined impact of the higher order slip with variable transverse magnetic field flow and thermal transport using Roseland’s heat flux of the Eyring–Powell fluid with assumption of boundary layer, on nonlinear stretching sheet, in which fluid is considered electrically conducting. The transformed ordinary differential equations are solved by three-stage Lobatto IIIa collocation finite difference scheme using MATLAB. The impact of pertinent flow parameters on dimensionless velocity and temperature profiles is presented graphically and discussed in detail. Obtained results confirm that excellent agreement is achieved for the limiting case with those from the available literature. It is found that skin friction increases in the presence of slip parameters, whereas the opposite behaviour is noted in the Nusselt 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".