Reliability based multidisciplinary design optimization of cooling turbine blade considering uncertainty data statistics
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Considering the coupling among aerodynamic, heat transfer and strength, a reliability based multidisciplinary design optimization method for cooling turbine blade is introduced. Multidisciplinary analysis of cooling turbine blade is carried out by sequential conjugated heat transfer analysis and strength analysis with temperature and pressure interpolation. Uncertainty data including the blade wall, rib thickness, elasticity Modulus and rotation speed is collected. Data statistics display the probability models of uncertainty data follow three-parameter Weibull distribution. The thickness of blade wall, thickness and height of ribs are chosen as design variables. Kriging surrogate model is introduced to reduce time-consuming multidisciplinary reliability analysis in RBMDO loop. The reliability based multidisciplinary design optimization of a cooling turbine blade is carried out. Optimization results shows that the RBMDO method proposed in this work improves the performance of cooling turbine blade availably.
KeywordsCooling turbine blade Reliability based multidisciplinary design optimization Kriging surrogate model Uncertainty data statistics
National Natural Science Foundation of China (Grant No. 51575444), Aerospace Science and Technology Foundation (Grant No. 2017-HT-XGD), Aviation Power Foundation (Grant No. 6141B090319) support this work.
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