Numerical Simulation of Particle Dispersion in the Wake of a Circular Cylinder
Bibliographic record
Abstract
In this article, numerical simulation of the Navier-Stokes equations was performed for the large-scale structures of a two-dimensional temporally developing cylinder flow and the associated dispersion patterns of particles were simulated. The time-dependent Navier-Stokes equations were integrated in time using a mixed explicit-implicit operator splitting rules. The spatial discretization was processed using spectral-element method. Non-reflecting conditions were employed at the outflow boundary. Particles with different Stokes numbers were traced by the Lagrangian approach based on one-way coupling between the continuous and the dispersed phases. The simulation results of the flow field agree well with experimental data. Due to the effects of the coherent structures, the particles demonstrate a more organized dispersion process in the space and a periodic dispersion characteristic in the time. Particle dispersion increases with the flow Reynolds number and so does for particle concentration, which is independent of particle size. However, for particles at different Stokes numbers, the dispersion patterns are different. The particles at smaller Stokes number congregate mainly in the vortex core regions and the particles at larger Stokes number disperse much less along the lateral direction with the even distribution. The higher density distribution at the outer boundary of large-scale vortex structure characterizes the dispersion pattern of particles at the Stokes numbers of order of unity. Furthermore, these particles disperse largely along the lateral direction and show the nonuniform distribution of concentration.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".