Investigation of the Effects of an Upstream Cavity on the Secondary Flow in Transonic Turbine Blade Passages with Endwall Contouring
Bibliographic record
Abstract
The investigation documented here aims to contribute to the understanding of secondary flows in modern high-pressure (HP) turbine blade passages.More specifically, it aims to improve the understanding of vortical structures near the endwall with respect to the presence of an upstream cavity that approximates the gap present in actual engines between the rotor and stator of an HP turbine.Further, it aims to assess the viability of using non-axisymmetric endwall contouring to reduce endwall losses, including those generated by the presence of an upstream cavity, using a modern airfoil, at HP turbine representative speeds and at off-design Mach numbers.To attempt to achieve this, a combination of flow measurement, flow visualization, and computational fluid dynamics (CFD) with linear turbine cascades was used.The test matrix consisted of three cases all with one common blade cascade geometry (SL2P).SL2P was combined with one of three endwalls: a baseline flat endwall, a flat endwall with a cavity incorporated upstream of the blade row, and a contoured endwall with the same upstream cavity geometry.A combination of pressure probes, pressure taps, and flow visualization were used to collect quantitative and qualitative data in a blow-down type wind tunnel.Complementary CFD studies were also carried out using the commercial CFD code ANSYS CFX.It was found that the presence of an upstream cavity can noticeably alter the structure and the strength of the secondary flow.When compared to the baseline flat endwall, measurements downstream of the trailing edge have shown a substantial increase in the size and strength of the passage vortex.The presence of the cavity also introduces a significant increase in the level of overturning.The secondary kinetic energy increased significantly due to the presence of the cavity, and a major effect on the overall losses was also evident, with the cavity endwall generating up to 14% higher mixed-out row losses I would like to acknowledge and thank my supervisor Dr. Steen A. Sjölander for his continuous support and guidance in completing this work.Special thanks to the professional staff of the Department of Mechanical and Aerospace Engineering for their technical assistance and contributions over the years.The technical expertise of Dr. Thomas Praisner and the financial contributions of Pratt & Whitney USA are also acknowledged.My deepest gratitude
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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 | 0.000 | 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".