Measurements and Computations of Compressible Flow Through a Turbine Cascade With Surface Roughness
Bibliographic record
Abstract
Experiments and computations have been carried out for a high-pressure turbine cascade having bands of roughness on the blade surfaces, for cascade-exit Mach numbers ranging from 0.4 to 1.13 Tests were carried out with three different relative roughness heights as well as with smooth surfaces. The results comprise profile-loss coefficients and deviation angle. Corresponding flow computations were done using the Fluent 6.0 CFD code with the Spalart-Almaras turbulence model and wall functions to model the near-surface flow. Good agreement was found between the experimental and computational results, especially with regard to trends with Mach number, roughness height and roughness-band configuration. This indicates that current computational methods, which use essentially the same approach to model surface-roughness effects as validated for incompressible flow, can give good predictions of compressible flow over rough surfaces, including details of the viscous flow field. The experimental data constitutes a valuable resource for future efforts to improve prediction capabilities for flows involving rough surfaces.
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.
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".