TY - JOUR
T1 - Performance-Driven Multi-Objective Optimization Method for DLR Transonic Tandem Cascade Shape Design
AU - Li, Kunhang
AU - Meng, Fanjie
AU - Wang, Kaibin
AU - Guo, Penghua
AU - Li, Jingyin
N1 - Publisher Copyright:
© 2022, Science Press, Institute of Engineering Thermophysics, CAS and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2023/1
Y1 - 2023/1
N2 - Transonic tandem cascades can effectively increase the working load, and this feature conforms with the requirement of the large loads and pressure ratios of modern axial compressors. This paper presents an optimization strategy for a German Aerospace Center (DLR) transonic tandem cascade, with one front blade and two rear blades, at the inlet Mach number of 1.051. The tandem cascade profile was parameterized using 19 control parameters. Non-dominated sorting Genetic algorithm (NSGA-II) was used to drive the optimization evolution, with the computational fluid dynamics (CFD)-based cascade performances correction added for each generation. Inside the automatic optimization system, a pressure boundary condition iterative algorithm was developed for simulating the cascade performance with a constant supersonic inlet Mach number. The optimization results of the cascade showed that the deflection of the subsonic blade changed evidently. The shock wave intensity of the first blade row was weakened because of the reduced curvatures of the optimized pressure and suction sides of the front blade part and the downstream moved maximum thickness position. The total pressure losses decreased by 15.6%, 20.9% and 19.9% with a corresponding increase in cascade static pressure ratio by 1.3%, 1.8% and 1.7%, for the three cascade shapes in the Pareto solution sets under the near choke, the design and near stall conditions, respectively.
AB - Transonic tandem cascades can effectively increase the working load, and this feature conforms with the requirement of the large loads and pressure ratios of modern axial compressors. This paper presents an optimization strategy for a German Aerospace Center (DLR) transonic tandem cascade, with one front blade and two rear blades, at the inlet Mach number of 1.051. The tandem cascade profile was parameterized using 19 control parameters. Non-dominated sorting Genetic algorithm (NSGA-II) was used to drive the optimization evolution, with the computational fluid dynamics (CFD)-based cascade performances correction added for each generation. Inside the automatic optimization system, a pressure boundary condition iterative algorithm was developed for simulating the cascade performance with a constant supersonic inlet Mach number. The optimization results of the cascade showed that the deflection of the subsonic blade changed evidently. The shock wave intensity of the first blade row was weakened because of the reduced curvatures of the optimized pressure and suction sides of the front blade part and the downstream moved maximum thickness position. The total pressure losses decreased by 15.6%, 20.9% and 19.9% with a corresponding increase in cascade static pressure ratio by 1.3%, 1.8% and 1.7%, for the three cascade shapes in the Pareto solution sets under the near choke, the design and near stall conditions, respectively.
KW - aerodynamic design
KW - cascade parameterization strategy
KW - performance-driven multi-objective optimization methodology
KW - transonic tandem cascade
UR - https://www.scopus.com/pages/publications/85142519765
U2 - 10.1007/s11630-022-1707-5
DO - 10.1007/s11630-022-1707-5
M3 - 文章
AN - SCOPUS:85142519765
SN - 1003-2169
VL - 32
SP - 297
EP - 309
JO - Journal of Thermal Science
JF - Journal of Thermal Science
IS - 1
ER -