Axial Dispersion in Nanofluid Poiseuille Flows Stirred by Magnetic Nanoagitators
Bibliographic record
Abstract
A Taylor–Aris dispersion in laminar capillary flows of magnetic nanofluids submitted to transverse rotating magnetic fields (RMFs) was analyzed with a simple phenomenological mixing approach. The nanofluid residence time distributions (RTDs) measured under RMFs were used to quantify the deviations, with respect to field-free Poiseuille flows, of the axial dispersion induced by the rotating magnetic nanoparticles (MNPs) as a function of MNPs concentration and diameter, and RMF frequency and strength. The attenuation of axial dispersion due to the magnetic field was ascribed to an enhanced transverse diffusion coefficient that thrust tracer radial transport, owing to nanoconvective streams in the nanoparticle neighborhoods, beyond molecular diffusion capability. To estimate the enhanced transverse diffusion coefficient, a semiempirical model was developed in which the nanofluid domain was viewed as an array of identical cells each containing a magnetic nanoparticle at its center. Owing to the nanoparticle rotation in the magnetic field, each cell consisted of an inscribed perfectly mixed core confined in a stagnant shell where molecular diffusion prevailed. Two- and three-dimensional diffusion simulations of the two-zone cell were used to quantify, and link, the size of the mixed core to the measured axial dispersion coefficients under various experimental conditions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".