Thermal irreversibility and bio-convective transport in a radiative Williamson hybrid nanofluid: application to solar-powered aircraft
Bibliographic record
Abstract
Solar energy, as the primary source of thermal radiation, plays a pivotal role in powering photovoltaic systems, solar panels, and advanced energy applications including hybrid nanofluids. With the growing integration of nanotechnology into aerospace systems, researchers are actively exploring its potential to enhance the thermal performance and operational efficiency of solar-powered aircraft. This study investigates the heat and mass transfer characteristics of both mono nanofluid (Cu/SA) and hybrid nanofluid (GO–Cu/SA) flowing over an extendable surface. The hybrid nanofluid is directed toward a parabolic trough embedded within the wings of a solar-powered aircraft, simulating realistic aerospace thermal conditions. Key effects such as viscous dissipation, inclined magnetic field, and thermal radiation are considered to evaluate heat transfer efficiency. Additionally, entropy generation in the flow of a Williamson hybrid nanofluid over an extensible sheet is analyzed to assess thermal irreversibility. The governing partial differential equations, derived from conservation laws, are transformed into ordinary differential equations (ODEs) using similarity variables. These ODEs are then solved numerically using the shooting method. The working fluid comprises sodium alginate as the base liquid, with copper and graphene oxide nanoparticles uniformly dispersed. Results are presented through graphical and tabular formats to illustrate variations in velocity, temperature, concentration, and motile microorganism density. Findings reveal that the Biot number enhances the heat transfer rate by approximately 40.60%–86.54% for the mono nanofluid (Cu/SA) and 39.90%–85.67% for the hybrid nanofluid (GO–Cu/SA). Moreover, the chemical reaction parameter increases the mass transfer rate by 21.53% in the mono nanofluid and 16.40% in the hybrid nanofluid. It is also observed that an increase in the velocity slip parameter leads to a reduction in entropy generation. The obtained results are validated against existing literature, confirming their accuracy and reliability.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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 teacher head, 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".