Optimization of Effusion Cooling Pitch With Non-Zero Compound Angle
Bibliographic record
Abstract
Abstract Realistic gas turbine combustors featuring swirling main flows impart additional lateral momentum to effusion cooling jets, inducing a non-zero compound angle and a varied effective pitch of effusion cooling holes. Our previous work investigated this directional effect by varying the compound angle at a fixed pitch while keeping the other cooling hole parameters identical. It was suggested that adopting a 45-degree compound angle at an optimal pitch could further enhance the adiabatic film cooling effectiveness (AFE). Building upon this foundation, the present study aims to experimentally determine the optimal pitch for effusion cooling holes with a 45-degree compound angle configuration. The compound angle was particularly selected for its previously demonstrated potential to balance the trade-off between coolant lateral spread and coolant-main flow mixing. The pitch optimization approach utilized individual effusion jets as foundation to achieve an enhanced effusion design with optimal coolant film coverage. Specialized test coupons with sparsely spaced 45-degree compound angle effusion cooling holes were designed and fabricated to evaluate the trajectories of individual effusion jets across a range of blowing ratios (BR). Two optimization methods were employed to determine the optimal pitch of individual effusion jets. The optimized pitch derived from individual effusion jets was subsequently adopted to design uniform effusion cooling test coupons with either inline or staggered alignments. The results were compared to the baseline configuration (δx = 7d, δy = 9d, staggered alignment), which was used in the prior work studying the directional effects. All measurements of adiabatic film cooling effectiveness (AFE) were obtained using a binary Pressure Sensitive Paint (PSP).
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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".