Modulation of Heat Flux by Inertial Particles Thermal Feedback in a Turbulent Shearless Anisothermal Flow
Bibliographic record
Abstract
We analyze the modulation of heat flux by particle thermal feedback in a turbulent shearless flow by employing a recently introduced decomposition of the velocity-temperature correlation in terms of particle velocity and temperature time derivative correlations.The results of a set of Eulerian-Lagrangian point-particle direct numerical simulations (DNSs) at a Taylor microscale Reynolds number equal to 56 and with the same volume fraction is used to reveal the action of thermal feedback in a wide range of thermal Stokes number and Stokes numbers.The results show that particle heat flux is influenced by thermal feedback more than fluid convective heat flux and they act in the opposite way in two-way coupling regime.We also discuss why global particle contribution to the heat flux ratio behave in a certain way and what statistics can attenuate or enhance this ratio under different particle inertia and thermal inertia.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".