URANS Investigation of Unsteady Wakes and Purged Hub Cavity Impact on the Aerodynamics of a High Speed Low-Pressure Turbine Cascade
Bibliographic record
Abstract
Abstract In low-pressure turbines, disc cooling avoids exposure to high temperatures which would reduce the lifetime of the component. Purge flow is injected in the endwall cavities to prevent ingestion of the hot main path gases and blows into the annulus upstream of the rotor blades. The interaction between purge and mainstream flows modifies the secondary flows arising in the blade passage. This paper analyses the predictions of the impact of periodic wakes and endwall cavity through unsteady Reynolds-Averaged Navier Stokes (URANS) simulations. The investigated experimental test case is the SPLEEN linear turbine cascade. The simulations are performed at the outlet design Reynolds number of 70,000 (based on the chord) and outlet design Mach number of 0.9. The influence of the unsteady wakes is investigated using time-accurate numerical results. The simulations show a periodic reduction of secondary flows and downstream losses. Time-averaged results evidence that the inclusion of the cavity and purge flow leads to significant changes in the topology of the secondary flows found in the blade passage. The egress flow contributes to the development of a strengthened and wider passage vortex consequently increasing the total pressure losses by 2.5% in the dominant loss core and leading to a spanwise migration of the structure of approximately 3.5% of the blade span. The numerical predictions of pressure fluctuations on the blade skin are compared to the experimental data to show the ability of URANS simulations to accurately predict the aerodynamics excitations on the blade.
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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) | 0.000 | 0.000 |
| 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".