Assessment of the Performances of RANS Models for Simulating Swirling Flows in a Can-Combustor
Bibliographic record
Abstract
The paper presents an assessment of the performances of RANS turbulence models for simulating turbulent swirling can-combustor flows with different inlet swirl intensities (i.e.S=0.4 and S=0.81).The predictions compared against published experimental data reveal that the eddy-viscosity models can not show the central recirculation zone in the case of a weakly swirling flow.However, although they reveal the existence of this region in a strongly swirling flow, they are incapable of predicting its correct size.On the other hand, the Reynolds stress models are able to predict the corner and the central recirculation zones in both flow cases.The predictions of turbulence intensities by using the realizable k-and the SST k-are comparable to those of the Reynolds stress closures.The shear stresses are not well predicted by all the tested models.Both the eddy-viscosity and the Reynolds stress closures show relatively less approximation errors in the weakly swirling flow.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".