Reynolds and Mach Number Dependence of Hypersonic Blunt Body Laminar Near Wakes
Bibliographic record
Abstract
Laminar separation on the aftbody of an adiabatic circular cylinder was numerically investigated over a range of freestream Mach and Reynolds numbers using the free open-source program OpenFOAM. Simulations were performed assuming laminar, continuum, thermally perfect flow of nitrogen gas. Simulation predictions have been compared to various empirical correlations in the literature. Empirical formulations were presented for the pressure minimum location, separation location, and separation length on the cylinder aftbody. The effects of both Mach and Reynolds numbers on the separation location were examined by correcting for the change in viscosity across the shock wave. This was accounted for explicitly in the presented empirical formulations by deriving an expression for the viscosity change across the shock. A free-interaction theory was used to examine the wall-pressure distribution due to lip-shock formation on the aftbody. Over a range of Mach and Reynolds numbers, it was found that the profile of a free-interaction parameter was predictable and nearly Reynolds number and Mach number independent. This free-interaction parameter was a correlation between the properties at the onset of the interaction and the ensuing pressure rise. This provided a means to predict the lip-shock formation, provided the boundary-layer properties at the pressure minimum were known.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".