Shower Head Film Cooling Effectiveness of a Symmetrical Turbine Blade Model: Effect of Lateral Injection
Bibliographic record
Abstract
The performance of the SSG Reynolds Stress Model for the prediction of film cooling at the leading edge of a symmetrical turbine blade model is investigated. The test case blade model is symmetric and has one injection row of discrete cylindrical holes on each side near the leading edge. In the present computation several blowing ratios of 45° lateral injection are tested and compared with previous streamwise computations. Further, film cooling effectiveness contours on the blade surface and lateral averaged adiabatic film cooling effectiveness are presented and compared with available measurements. In addition to validation data, several longitudinal and transversal contours and vector planes are reproduced and clearly found to underscore the anisotropic turbulent field occurring in the present shower head film cooling configuration. The advantage of lateral versus streamwise injection is highlighted by the destruction of the two contra rotating vortices which are responsible of cooling effectiveness decrease. In case of lateral injection only one vortex is found and the flow structure is radically different from that known by streamwise jet in cross flow.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".