TY - JOUR
T1 - Reliability based multidisciplinary design optimization of cooling turbine blade considering uncertainty data statistics
AU - Li, Lei
AU - Wan, Huan
AU - Gao, Wenjing
AU - Tong, Fujuan
AU - Li, Honglin
N1 - Publisher Copyright:
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/2/15
Y1 - 2019/2/15
N2 - 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.
AB - 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.
KW - Cooling turbine blade
KW - Kriging surrogate model
KW - Reliability based multidisciplinary design optimization
KW - Uncertainty data statistics
UR - http://www.scopus.com/inward/record.url?scp=85053695210&partnerID=8YFLogxK
U2 - 10.1007/s00158-018-2081-5
DO - 10.1007/s00158-018-2081-5
M3 - 文章
AN - SCOPUS:85053695210
SN - 1615-147X
VL - 59
SP - 659
EP - 673
JO - Structural and Multidisciplinary Optimization
JF - Structural and Multidisciplinary Optimization
IS - 2
ER -