RANS Analysis of Merging Supersonic Streamwise Vortices for Enhanced Mixing in Scramjet Combustors
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2022-1410.vid Streamwise vortices are studied as a mixing enhancer for scramjet combustors due to their insensitivity to compressibility relative to spanwise structures. A specific merging interaction between supersonic corotating vortices has been shown in experiments to sustain turbulence production against decay. In this paper this interaction is investigated numerically to determine how well it can be replicated with a RANS approach, and the effect of increasing the Mach number. The shape and rotation of the merging vortices appears similar to experimental results. The decay of vorticity follows a similar trend to experimental results, however the vorticity was higher in the RANS results. At higher Mach numbers the merging process appears to be pushed further down the domain
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".