Multidisciplinary probabilistic and robust design optimization for turbine blade

To investigate a suitable multidisciplinary design optimization method for turbine blade considering uncertainty, a multidisciplinary six sigma probabilistic and robust design optimization method for turbine blade was presented. Multidisciplinary feasible (MDF) method was used to decouple the multidisciplinary analysis and second order Taylor expansion method was employed to measure the mean and standard deviation of variables. The Kriging approximate model with updating was introduced to reduce the computational cost of MDF. The case study shows that the proposed method can make the design reach the best performance with desired reliability and robustness. The reliability and robustness are improved compared to deterministic multidisciplinary design optimization. It indicates that the proposed method is available and feasible for the engineering application.