Film holes in first stage turbine nozzle work under high uncertainty conditions. The main source of uncertainty is arising from the manufacturing tolerance and changeable flow conditions of turbine inlet and cooling system. In this study, three separate robust design optimization studies for film cooling hole array are performed under consideration of manufacturing and operational uncertainties. To determine the design variables, film hole array is parameterized by newly suggested shape function by five design variables. Efficient Design Optimization method coupled with kriging model and Monte Carlo Simulation, and Genetic Algorithm are used as robust design optimization methods. Manufacturing tolerance and blowing ratio variance of film hole, and turbine inlet temperature profile are considered as uncertainty and probabilistic density function and variation range of these uncertainties are quantified by few random variables referring to the open literature. As a result, film hole array showing high cooling performance as well as robustness to the uncertainties are obtained and the results are compared: variation of turbine inlet temperature profile is less influential to the film cooling performance than other two uncertainties and random variables related to the holes located in upstream region has lager impacts on the cooling performance than the others.
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