TY - GEN
T1 - Multi-objective aerodynamic and stealthy performance optimization for airfoil using Kriging surrogate model
AU - Liao, Yanping
AU - Liu, Li
AU - Long, Teng
PY - 2011
Y1 - 2011
N2 - The Class-Shape function Transformation (CST) method is used to describe the parameterized airfoil geometry. The parameterized models for aerodynamic and stealthy performance of airfoil are constructed. The aerodynamic analysis model of airfoil is constructed by Computational Fluid Dynamics (CFD) method based on N-S equations. And the stealthy performance analysis model of airfoil is constructed by Computational Electromagnetic Method (CEM) based Method of Moments (MoM). The multi-objective aerodynamic and stealthy performance optimization method for airfoil using Kriging surrogate model is presented in this paper. The Latin hypercube method is employed to get a set of sample points. The aerodynamic and stealthy performance Kriging models are built. The multi-objective aerodynamic and stealthy performance optimization of airfoil is optimized by combining Pareto genetic algorithm with Kriging surrogate model. The presented method is validated by two applications. The results of the investigation show that the constructed analysis models are reasonable and the presented multi-objective optimization design method is feasible, which can improve the performance of airfoil and the efficiency of optimization effectively.
AB - The Class-Shape function Transformation (CST) method is used to describe the parameterized airfoil geometry. The parameterized models for aerodynamic and stealthy performance of airfoil are constructed. The aerodynamic analysis model of airfoil is constructed by Computational Fluid Dynamics (CFD) method based on N-S equations. And the stealthy performance analysis model of airfoil is constructed by Computational Electromagnetic Method (CEM) based Method of Moments (MoM). The multi-objective aerodynamic and stealthy performance optimization method for airfoil using Kriging surrogate model is presented in this paper. The Latin hypercube method is employed to get a set of sample points. The aerodynamic and stealthy performance Kriging models are built. The multi-objective aerodynamic and stealthy performance optimization of airfoil is optimized by combining Pareto genetic algorithm with Kriging surrogate model. The presented method is validated by two applications. The results of the investigation show that the constructed analysis models are reasonable and the presented multi-objective optimization design method is feasible, which can improve the performance of airfoil and the efficiency of optimization effectively.
KW - Class-Shape function Transformation method
KW - Kriging surrogate model
KW - Multi-Objective optimization
KW - Pareto genetic algorithm
KW - Radar cross section
UR - https://www.scopus.com/pages/publications/80053141217
U2 - 10.1109/ICCSN.2011.6013971
DO - 10.1109/ICCSN.2011.6013971
M3 - Conference contribution
AN - SCOPUS:80053141217
SN - 9781612844855
T3 - 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011
SP - 569
EP - 574
BT - 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011
T2 - 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011
Y2 - 27 May 2011 through 29 May 2011
ER -