Quantifying instantaneous flow reversal of tracer particles in subsonic, transonic and supersonic flows past a circular cylinder
Bibliographic record
Abstract
Tracer pathline statistics have rarely, if at all, been used in the investigation of compressible subsonic, transonic and supersonic flows past a circular cylinder. Here, we report pathline histogram, conditional histogram and zonal histogram data, focusing on the characteristics of particle instantaneous flow reversal and their dependencies on Mach number and tracer release position. The far-upstream Mach number and the diameter-based Reynolds number used for these three flow regimes are (0.2,10000),(0.9,3900) and (1.2,10000), respectively. The subsonic surface-release histogram profiles display unexpected persistent oscillations at a frequency 50 times of the periodic vortex shedding frequency, reflecting the effect of a very small magnitude zig-zagging type of particle motion in a region very close to the wall and slightly behind the mean flow separation location. No similar high-frequency oscillation is observed in the corresponding transonic and supersonic histograms likely because, at Ma≥0.9, periodic vortex shedding ceases to exist and the near-wake becomes a quasi-laminar recirculation zone bounded by a pair of converging slip-layers with a neck opening to the far-wake. At the instant of 5 subsonic vortex-shedding periods after being released from the cylinder surface, there are 1.67%, 35.2% and 39.7% particles that experience flow reversal in the subsonic, transonic and supersonic flows, respectively. Surprisingly, in the present transonic flow, growth of the turbulent far-wake behind the pair of lambda-shocks is constrained over a considerable streamwise distance.
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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 | 0.000 | 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 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".