Analysis on flow features of unsteady Williamson fluid inaugurated by melted wedge in the presence of heat generation–absorption: an extensive computational study
Bibliographic record
Abstract
After various thought-provoking experimental and theoretical investigations on heat transfer characteristics of usual liquids, researchers recommended the idea of inclusion of nano-sized structures into host liquid. This idea yielded a tremendous revolution in the world of fluid mechanics and brought researchers’ and scientists’ attention in this direction. The present paper is addresses enhancing the unique flow features of Williamson fluid by the inclusion of nano-sized particles. The Williamson fluid model along with prominent factors like magnetic field, heat generation–absorption, stagnation point, and active heat–mass flux are considered over a wedge. The mathematical formulation for the concerned problem is addressed in the form of a system of ordinary differential equations under acceptable governing laws. The attained system of coupled equations is hard to solve analytically. Therefore, a self-coded algorithm known as the shooting method is executed to report a numerical solution. A graphical representation of pertinent profiles and the parameters that affect them are included. Tabular and graphical trends present the influence of involved variables on Williamson momentum conservation and thermal and mass fields. In addition, the physical quantities at the surface of the wedge are also examined. In addition, reliability of the current work is established by constructing a comparison for skin friction values with the published literature. Our result indicates that increment in unsteadiness parameter causes temperature and concentration drop of flowing fluid over the wedge, whereas a positive effect on momentum profile is manifested. Furthermore, viscosity ratio parameter tends to follow the temperature and increase the velocity field. Magnetic field controls the turbulence by decreasing the velocity and increases the temperature. Accelerating behavior in velocity field and diminishing pattern in velocity is portrayed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".