Magnetohydrodynamic nonlinear mixed convection flow of reactive tangent hyperbolic nano fluid passing a nonlinear stretchable surface
Bibliographic record
Abstract
Abstract The intent of this paper is to unravel the transport of a nonlinear mixed convection tangent hyperbolic nanofluid along a nonlinear stretchable sheet in the neighbourhood of a stagnation point. The impacts of magnetohydrodynamic, thermophoresis, Brownian motion and activation energy together with non-uniform heat source associated with varying thermal conductivity are scrutinized. The outlining transport equations are mutated into a system of nondimensional ordinary differential equations by the use of similarity transformations and then tackled with the Runge–Kutta Fehlberg coupling shooting method. The impact of all essential parameters in respect of the dimensionless quantities are graphically exhibited and deliberated. The significant consequences of the investigation are that increment in the Darcy with magnetic term declines the flow velocity while that uplift the fluid temperature. The skin friction factor triggers a considerable increase with the power-law exponent and magnetic field parameters. The intensity of heat and mass transfer shrink with hike in the values of the thermophoresis parameter. The vetting of the numerical solution is done with earlier related studies in the limiting position and presented in tabular form showing perfect correlation.
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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 | 0.000 |
| 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".