Performance of RANS models for simulating turbulent swirling and free jet flows
Bibliographic record
Abstract
The present work aims at assessing the perforrnances of RANS turbulence models for simulating turbulent swirling and free jet flows, using the commercial software FLIIENT version 6.I.22.The RANS turbulence models examined are grouped into two families: (l) the two-equation eddy-viscosity models, which are the k-e, RNG k-c, realizable k-t, and the ^9^SZ k-ø, and (ii) the Reynolds stress models, which are the standard .RSM and the ,S,SG.The first flow case simulated in this thesis is a turbulent swirling flow in a can- combustor, in which two inlet swirl intensities (i.e.,S:0.4 and ,5:0.81) are considered.The predictions compared against published experimental data revealed that the eddyviscosity models are unable to capture the central recirculation zone in the case of the weakly swirling flow (,S:0.4).However, although they revealed the existence of this feature for the strongly swirling flow (5:0.81),they were incapable of predicting its correct size.On the other hand, the Reynolds stress models were able to predict the corner and the central recirculation zones for both swirl intensities.The predictions of turbulence intensities by using the realizable k-e and the SST k-a were comparable to those of the Reynolds stress closures.The shear stresses were not well predicted by all the tested models.Both the eddy-viscosity and the Reynolds stress closures showed relatively less approximation errors in the weakly swirling flow.The second flow case examined is a turbulent free jet issuing from a sharp-edged equilateral triangular orifice in still air surrounding.The numerical simulations revealed that among the eddy-viscosity models, the performance of the reqlizctble k+ model is comparable to that of the Rel.nolds stress models with the exception of the predictions of iii the turbulence intensities.The vena contracta effect was predicted by all the tested models' The Æ-e and the RNG k+ models showed faster and slower mixing than that of the experiment, respectively.On the other hand, the Reynolds stress models, especially the standard RSM, appeared to produce better predictions than the eddy-viscosity models.However, the standard RSM seemed unable to capture accurately enough the flatness of the streamwise velocity profiles (top-hat profile) near the centreline in the near-field.The third and last flow case examined in the present thesis is a turbulent free jet issuing from a circular nozzle with a triangular collar.In this exercise, only the standard RSM and the standard Æ-e model are employed.This is because the trends seen in the combustor and the triangular orifice studies suggested that in these geometries the standard R,SM has the potential of producing results that agree remarkably well with experimental data.Whereas the standard /r-e model is used as a simple representative of the two-equation eddy-viscosity models.This flow case, a circular nozzle which is connected to a triangular collar with a step, may be regarded as a combination of the previous geometries.This is because it encompasses both confinement and sudden expansion.The predictions revealed that the standard, RSM, which requires more computational time than does the standard k-e model, is capable of reproducing remarkably well the experimental results.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".