Darcy–Forchheimer dynamics of hybrid nanofluid due to a porous Riga surface capitalizing Cattaneo–Christov theory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to superior heat transport offered by hybrid nanofluids compared to traditional nanofluids, an investigation on the dynamics of a hybrid nanofluid consisting of (Fe3O4+Al2O3)/water over a porous Riga stretching surface using the double-diffusion theory of Cattaneo–Christov is investigated. The hybrid mixture (Fe3O4+Al2O3) is placed in a Darcy–Forchheimer-porous-medium, and the significance of Brownian and thermo diffusions are also taken into account. The thermophysical attributes of solid particles and base fluid are used to model the problem along with the basic transport equations of fluid dynamics. Similarity transformations are used to make the transport equations dimensionless. The final version of the coupled boundary value problem is then numerically solved via RKFST (Runge–Kutta–Fehlberg method based on shooting technique). The post-processing of the solution involves computing the velocity field, skin-friction, Nusselt number, Sherwood number, temperature field, streamlines, isotherms, and concentration field against various estimations of the involved parameters. The streamlines and isotherms are observed to be more effective for the hybrid nanofluid than the nanofluid, whereas the temperature is reduced for the hybrid nanofluid compared to the nanofluid. Temperature is reduced with the development of thermal-relaxation multiplier, while concentration is also declined with the higher estimation of concentration-relaxation multiplier.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 0.001 |
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 it