Interaction of a Particle-Laden Gaseous Jet with a Confined Annular Turbulent Flow
Bibliographic record
Abstract
A numerical analysis of polydispersed glass particles interacting with a confined turbulent bluff-body flow was performed by combining the finite-volume method for the gaseous flow with a mesh-free Lagrangian approach for the particulate flow. Three turbulence-closure models, namely the Reynolds-stress, the standard k-ϵ, and the nonlinear k-ϵ models, were first comparatively studied for the single-phase flow. The second-moment Reynolds-stress model was then selected for the prediction of the turbulent gaseous flow in a gas-particle system, where an improved eddy-interaction model was used to predict turbulence-induced particle dispersion. The interaction between the two phases was accounted for through coupling source terms. Numerical predictions of two-phase mean and fluctuating velocities for particle sizes ranging from 15 to 115 μm were compared with corresponding experimental data. Reasonably good agreement was achieved for the mean properties of both the gaseous and particulate flows.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".