Three-dimensional numerical investigation of a suspension flow in an eccentric Couette flow geometry
Bibliographic record
Abstract
This paper investigates the influence of eccentricity on flow characteristics and particle migration in Couette geometries. The study involves numerical simulations using the recent frame-invariant model developed by Badia et al. [J. Non-Newtonian Fluid Mech. 309, 104904 (2022)]. The study begins with a two-dimensional analysis, focusing first on the Newtonian fluid in order to thoroughly characterize the specific properties of this flow configuration. Next, the impact of eccentricity on particle migration in an isodense suspension is examined by numerical simulations based on the experiments conducted by Subia et al. [J. Fluid Mech. 373, 193–219 (1998)]. Furthermore, the study is extended to include a full three-dimensional analysis of a dense suspension flow in an eccentric Couette geometry based on resuspension experiments conducted by Saint-Michel et al. [Phys. Fluids 31, 103301 (2019)] and D'Ambrosio et al.[J. Fluid Mech. 911, A22 (2021)]. The main objective of the latter study is to investigate the influence of eccentricity on the resuspension height and on the calculation of the particle normal stress in the vertical direction through the volume fraction profile analysis. Our results show that even minimal eccentricity can lead to significant changes compared to the centered case.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".