A review of Reynolds-averaged Navier–Stokes modeling for hypersonic large cone–flares
Bibliographic record
Abstract
This work assesses the status of Reynolds-averaged Navier–Stokes' (RANS) predictive capability for axi-symmetric hypersonic geometries. An in-depth literature review on the topic is provided including relevant developments in the field of RANS for these types of setups. Furthermore, as part of the Applied Vehicle Technology-352 on hypersonic turbulence, a code-to-code comparison on two large cone–flare geometries, experimentally studied at Calspan-University of Buffalo Research Center, has been performed to evaluate the variability in predictions for freestream Mach numbers ranging between 5 and 13 at low enthalpy conditions. The nature of the physics found in cone–flare geometries is known to be extremely challenging for RANS computational fluid dynamics codes, a fact that is confirmed in this work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".