Numerical investigation of MHD Prandtl melted fluid flow towards a cylindrical surface: comprehensive outcomes
Bibliographic record
Abstract
In this work, we explore the mathematical structuring of Prandtl fluid flow towards an inclined stretched cylinder. Modelling of this newly proposed model is manifested in three different ways. A momentum equation for the concerned model is established under the role of an induced Lorentz field, whereas the thermal and mass transport mechanisms account for the role of the heat generation–absorption process and chemical reaction phenomenon. For a more realistic and schematic analyses of the present problem, the field expressions are expressed mathematically in terms of PDEs. The obtained intricate differential system is converted into ODEs by means of transformations. Improved numerical simulation is conducted using the Cash and Carp method to foresee the pattern of thermophysical distribution towards existing involved constraints. It is noticed that Prandtl fluid velocity declines for increases in both the Prandtl fluid parameter and elastic parameter. Further, the fluid temperature increases the effects of the magnetic field, curvature, and the melting parameters while the concentration profile shows decline curves for both the Schmidt and chemical reaction parameters. It is important to note that this nature is preserved for both the magnetized and non-magnetized cases.
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.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".