Viscous capturing of heated particles in one- and two-way coupledturbulence
Bibliographic record
Abstract
Abstract: Inertial particles are known to form clusters in turbulence. In this regard, the previous literature employs a dimensionless parameter, Stokes number (St), for characterizing particle clustering. However, it was recently found that in heated particle-laden flows, temperature-driven fluid viscosity causes the particle clustering to depart from their St based behaviour, and deliver higher clustering than the classical predictions. This is due to a phenomenon called viscous capturing (VC), where particles locally get captured by viscous gas clouds upon heating which results in greater clustering. The aim of this study is to use Direct Numerical Simulations (DNS) for testing VC in one-way coupling (OWC) and two-way coupling (TWC) in momentum, to understand the validity of VC. It is found that the VC holds well even in TWC, where particle are capable of resisting VC. Hence, VC should be considered an important parameter in clustering sensitive thermal applications, along with St.
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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".