On steady two-dimensional Carreau nanofluid flow in the presence of infinite shear rate viscosity
Bibliographic record
Abstract
This paper examines the steady two-dimensional Carreau nanofluid flow over a stretching surface with infinite shear rate viscosity. The effects of Brownian motion and thermophoresis under the influence of convectively heated surface are analyzed. Using suitable transformations, nonlinear partial differential equations are transformed into ordinary differential equations and solved numerically using the Runge–Kutta–Fehlberg method coupled with the shooting technique. The effects of various physical parameters like local Weissenberg number (We), thermophoresis parameter (Nt), Brownian motion parameter (Nb), Prandtl number (Pr), Lewis number (Le), viscosity ratio parameter (β*), and Biot number (γ*) on the temperature and nanoparticle concentration distributions are displayed graphically and discussed quantitatively. Generally, our results reveal that temperature and nanoparticle concentration distributions are marginally influenced by the viscosity ratio parameter. Further, it is noted that augmented values of viscosity ratio parameter thin the boundary layer thickness in shear thinning fluid and the reverse is true for shear thickening fluid.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".