Compressor Tip Leakage Mechanisms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The over tip leakage flow in an unshrouded compressor blade row is highly three dimensional, yet in order for aerodynamicists to analyze and improve designs, they must be able to simplify the problem down to a limited number of mechanisms. In this article, the behaviors of the dominant loss mechanisms are investigated using a multi-order methodology that combines rapid experimental tests of different geometries, detailed measurements in a large rotating rig, large numbers of industry-standard 3D Reynolds-averaged Navier–Stokes (RANS) simulations, and a single direct numerical simulation (DNS) of the datum geometry. The three loss mechanisms identified are ultimately caused by mismatches in flow velocity: separation of the flow as it enters the gap, mixing of the leakage jet with the mainstream close to the suction surface, and endwall shear acting on the jet itself at mid passage. This article is presented in three sections: First, the loss mechanisms are visualized and examined in detail using experiment, simulation, and models. Second, the uncertainty in industry-standard predictions is analyzed and improvements to turbulence modeling are presented. Finally, a matrix of blades with different 3D designs is used to investigate the balance of loss mechanisms and a reduction in total loss generation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it