Organized Streamwise Vorticity on Convex Surfaces With Particular Reference to Turbine Blades
Bibliographic record
Abstract
Experiments were conducted on the flow through a transonic turbine cascade and at\nsubsonic speeds past a circular cylinder in cross-flow. These followed extensive work on\nvortex shedding behind these bodies, displaying the phenomena of energy separation at\nsubsonic speeds; the turbine blades also exhibited exotic vortex-shedding modes in transonic\nflow. Surface flow visualization was undertaken on the suction surface of the turbine blade\nand on the circular cylinder. This was effective in providing a time-average mapping of the\nvortical structures within the blade passage and around the cylinder. The usual phenomena\nof horseshoe vortices, secondary flows, passage vortices and wall and corner vortices were\nobserved. In addition, and more surprisingly, organized systems of fine-scale streamwise\nvortices were observed for both cases. Under the influence of the strong favorable pressure\ngradients on the turbine blade suction surface, the vortices persisted to the trailing edge. For\nthe circular cylinder work, undertaken at an inlet Mach number of 0.5, the streamwise\nvortices occupied the forward portion of the cylinder, almost to the 83 degree azimuth, and\nre-appeared after laminar separation. This streamwise vorticity had been predicted and\nobserved previously for low speed flows, with attendant theories for wavelength. The\npresent results have been compared with the predictions giving reasonable agreement.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".