Extending the Capabilities of a High-Speed Wind Tunnel to Secondary Flow Measurements in Transonic Linear Turbine Cascades
Bibliographic record
Abstract
Since its commissioning, the Carleton University High-Speed Wind Tunnel has been used extensively for midspan aerodynamic measurements in transonic axial turbine cascades. Recently, a requirement has arisen to obtain three-dimensional, endwall flow data in turbine cascades in this facility. Three dimensional loss measurements in high-speed turbomachinery cascades and rotating rigs have often been obtained using Kiel probes. These probes have the advantage of giving direct measurements of the total pressures, thus allowing losses to be obtained with minimal data reduction and without resort to complex probe calibrations. On the other hand, they cannot be used to obtain flow direction and local estimates of static pressure. As a result they do not permit other important information to be obtained, such as secondary kinetic energy, axial velocity and vorticity distributions. This limits the ability to gain physical insights into the flow behaviour. An alternative to Kiel probes is the multi-hole pressure probe. The present study was intended to develop the ability to obtain detailed three-dimensional flow field measurements in our facility using primarily a seven-hole pressure probe. The measurements are compared with the equivalent total pressure measurements obtained with a Kiel probe of similar spatial resolution. The uncertainty in losses introduced by the processing of multiple pressure-port measurements, and the use of complex probe calibration data, is weighed against the advantages of the more detailed flow field data that are obtained. The results from two linear turbine cascades with different Zweifel coefficients are presented here. The results contribute a small addition to the data available on the effects of compressibility on secondary flows. Planned measurements will make substantial contributions in that direction in the future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".