Non‐Newtonian blood flow with magnetic nanoparticles in a W‐shaped stenosed arterial segment: A numerical study
Bibliographic record
Abstract
Abstract Flow of blood, infused with magnetic nanoparticles, in a W‐shaped stenosed human arterial segment is studied numerically using a realistic non‐Newtonian blood rheology model. It is observed that the Newtonian model predicts less time to reach a steady state than the non‐Newtonian blood rheology model. An increased drug retention time at the target site with an increase in nanoparticle concentration is predicted. Detailed simulations further reveal that the skin friction coefficient does not increase significantly with the increase in nanoparticle concentration. Hence, it is anticipated from our study that the infusion of drug‐carrying nanoparticles in blood flow does not excessively enhance wall shear stress that may lead to arterial wall damage. An overall increase in heat transfer rates and wall shear stress at the stenosed section is seen with an increase in Reynolds number. The present study provides valuable information for designing computer‐assisted drug delivery systems.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".