Irreversibility intent triple diffusion stream over porous medium plate with radiation and joule heating
Bibliographic record
Abstract
The influence of thermal radiation and Joule heating on the entropy inception by triple diffusion over the permeable plate is examined, as well as its influence on other physical aspects of the problem. The radiative and Joules heating effects are being investigated using a mathematical model. The irreversibility caused variations in entropy inception due to fluid, heat fluxes, and solute concentration of salts utilized. The non-dimensioned modeled equations were interpreted numerically by shooting approach using Runge-Kutta-Fehlberg scheme. Numerical outcomes were plotted in the form of graphs for flow and thermal distributions, entropy inception rate, and Nusselt number because of suction/injection through the plate, and the results of concentration based parametric analysis were plotted out for local entropy inception rate, local Bejan number, local mass Bejan number and local irreversibility ratio based on assisting flow and opposing flow. Local mass Bejan number underwent some interesting aspects, such that it behaves opposite to local Bejan number to enhance for magnetic, radiation parameter in suction/injection situations. In the suction/injection flow conditions, the entropy inception rate gets enhanced for most of the flow and thermal parameters like magnetic, radiation, convective parameters, Eckert number, buoyancy parameters of solutes 1 and 2, and temperature ratio parameter. Because of influences of assisting and opposing flow, the entropy inception rate gets slowed down by the effects of Lewis numbers of solutes 1 and 2 and Darcy number. Reynolds number has the influence assisting the entropy rate to increase.
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 | 0.000 |
| 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 | 0.000 |
| 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 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".