Evaluations and Modifications on Reynolds Stress Model in Cyclone Simulations
Bibliographic record
Abstract
Abstract The prediction performance of the Reynolds stress model (RSM) on the flow field in a cyclone has been validated by using particle imaging velocimetry (PIV) experimental results. The validations mainly focus on two features of the flow information with averaged and fluctuating flow fields, which can mostly reflect the turbulent flow properties in the cyclone. The comparisons between predictions and measurements show that the RSM has good performance on the averaged flow field prediction, especially on the prediction of the mean tangential velocity. However, for the fluctuating flow field, the prediction performance of RSM is rather poor. The predicted root mean square (RMS) velocities are greatly underestimated. The standard model coefficients used in RSM have to be modified to enhance its accuracy when used to predict the fluctuating structure of the strong swirling flow in the cyclone. The recommended model coefficients give much better predictions on the fluctuating flow field than the standard coefficients, without decreasing the prediction accuracy on the mean flow field.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".