Reynolds Stress Model in the Prediction of Confined Turbulent Swirling Flows
Bibliographic record
Abstract
Strongly swirling vortex chamber flows are examined experimentally and numerically using the Reynolds stress model (RSM). The predictions are compared against the experimental data in terms of the pressure drop across the chamber, the axial and tangential velocity components, and the radial pressure profiles. The overall agreement between the measurements and the predictions is reasonable. The predictions provided by the numerical model show clearly the forced and free vortex modes of the tangential velocity profile. The reverse flow (or back flow) inside the core and near the outlet, known from experiments, is captured by the numerical simulations. The swirl number has been found to have a measurable impact on the flow features. The vortex core size is shown to contract with the swirl number which leads to higher pressure drop, higher peak tangential velocity, and deeper radial pressure profiles near the axis of rotation. The adequate agreement between the experimental data and the simulations using RSM turbulence model provides a valid tool to study further these industrially important swirling 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".