Irreversibility analysis of Cu-TiO2-H2O hybrid-nanofluid impinging on a 3-D stretching sheet in a porous medium with nonlinear radiation: Darcy-Forchhiemer's model
Bibliographic record
Abstract
The current research is conducted to investigate the slip effect and to analyze entropy production in both hybrid nanofluids, and common nanofluids flow past a convectively heated three-dimensional stretching sheet placed in a porous medium. The slip flow is considered in a Darcy-Forchheimer's scheme by incorporating the nonlinear thermal radiation. Water is taken as base fluid, while Copper and Titanium dioxide nanoparticles are considered. The governing models are overset into dimensionless variables using similarity transformation, and the solution is acquired numerically. The impacts of pertinent factors on the flow, heat transfer, and entropy generation rates are explored. Additional plot portraying the streamlines and isotherms for both nanofluids are presented to examine the hydrothermal behavior. Skin friction and heat transport are discussed with sensible judgment. A comparison with earlier studies is unwrapped to ensure the model's validity. The results communicate that temperature is enhanced with porosity, whereas velocity is found to be decelerated. Bejan number is decreasing with an increase in the nanoparticle volume fraction of nanoparticles. Furthermore, hybrid nanofluids generate less entropy than common nanofluids.
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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 | 0.001 | 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".