Viscosity-driven clustering of heated polydispersed particles in subsonic jet flows
Bibliographic record
Abstract
The clustering of heated particles is known to increase with the rise in local gas viscosity , even at particle Stokes number S t < 1 . Despite being a dominant effect that holds in two-way coupling (TWC), this rise in clustering has been only probed in a triply periodic box via direct numerical simulations (DNS), in which the flow evolves temporally and the total volume (and mean fluid density) is fixed. We conduct DNS to study the dispersion of heated polydispersed particles in a spatially developing subsonic confined jet flow, where energy and momentum are modeled with TWC. Although there is only a 16 % increase in gas viscosity in the heated particle-laden simulation, it is sufficient to limit the particles within the central hot region of the jet. The particles traveling laterally start clustering at a thermal front created at the outer periphery of the jet. Thus, their lateral dispersion is also limited. Despite starting with the same S t values as their unheated counterparts, the heated particles yield more concentrated clusters within the jet as the number of heated particles declines sharply in the lateral direction . This is a compounding effect, where the presence of particles within the jet can produce more significant thermal changes inside the jet, which can further restrict the lateral movement of the particles. Experiencing identical eddies inside the jet causes particles of all sizes in the heating case to cluster at similar locations in the domain. These findings can considerably aid applications such as targeted drug delivery and cold spray coating techniques .
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".