Optimization of Film Cooling Holes on the Suction Surface of a High Pressure Turbine Blade
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Bibliographic record
Abstract
This paper aims to optimize film coolant flow parameters on the suction surface of a high-pressure gas turbine blade in order to obtain an optimum compromise between a high film cooling effectiveness and a low aerodynamic loss. An optimization algorithm coupled with three-dimensional Reynolds-averaged Navier Stokes (RANS) analysis is used to determine the optimum film cooling configuration. The VKI blade with two staggered rows of axially oriented, conically flared, film cooling holes on its suction surface is considered. Two design variables are selected; the coolant to mainstream temperature ratio and total pressure ratio. The effect of varying these coolant flow parameters on the film cooling effectiveness and the aerodynamic loss is analyzed using an optimization method and three dimensional steady CFD simulations. The optimization process involves a genetic algorithm and a response surface approximation of the artificial neural network type to provide low-fidelity predictions of the objective function. The CFD simulations are performed using the commercial software CFX. The numerical predictions of the aerodynamics and wall heat transfer are validated against experimental data. The optimization objective consists of maximizing the spatially averaged film cooling effectiveness and minimizing the aerodynamic penalty produced by film cooling. The results of this optimization are reported in terms of the aerodynamic loss and adiabatic cooling effectiveness.
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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