Spherical particle migration evaluation in low reynolds number couette flow using smooth profile method
Bibliographic record
Abstract
An Eulerian-Lagrangian model is developed to investigate the solid particle migration in low Reynolds number shear flows between two parallel plates. A continuous kernel function with a predefined thickness is applied in the implemented numerical model to smooth the discontinuity at the interface between primary and secondary phases. At each time step, the solid particle's rotation and displacement are calculated to directly capture the interaction between the solid particle and primary liquid phase without simplification. Solution verification is performed using the global deviation grid convergence index approach. The observed order of accuracy for the primary phase solver approaches 2, consistent with the formal order of accuracy of the applied discretization scheme. The obtained velocity profiles from the implemented numerical approach show a good agreement with the analytical solution, confirming the single-phase flow solver's reliability. The obtained numerical results from the applied Eulerian-Lagrangian multiphase model are also compared with experimental data from a linear shear flow apparatus with suspended buoyant particles, and good agreement was found.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".