Aiming at optimizing the head shape of the CRH3 high speed train, an efficient optimization approach is proposed. The CFD analysis by solving Navier-Stokes equations is coupled with optimization calculation based on t...Aiming at optimizing the head shape of the CRH3 high speed train, an efficient optimization approach is proposed. The CFD analysis by solving Navier-Stokes equations is coupled with optimization calculation based on the multi-objective genetic algorithm, meanwhile the arbitrary shape deformation technique (ASD) is also introduced into the design flow, which greatly shortens the time consumption for geometry regeneration and flow field remeshing. As a result, the efficiency of the optimization calculation is highly improved. Statistical analysis is done to the designs in the design space, and the correlation between the design variables and the objective is studied to find out the key variables that most affect the objective. Response surface analysis is also performed to get the nonlinear relationship between the key design variables and the objective with the Kriging algorithm. Finally, after the optimization, an aerodynamic performance comparison between the optimal shape and the original shape reveals that the original shape of CRH3 high speed train owns a very stable aerodynamic performance and can be trustingly used in industry.展开更多
文摘Aiming at optimizing the head shape of the CRH3 high speed train, an efficient optimization approach is proposed. The CFD analysis by solving Navier-Stokes equations is coupled with optimization calculation based on the multi-objective genetic algorithm, meanwhile the arbitrary shape deformation technique (ASD) is also introduced into the design flow, which greatly shortens the time consumption for geometry regeneration and flow field remeshing. As a result, the efficiency of the optimization calculation is highly improved. Statistical analysis is done to the designs in the design space, and the correlation between the design variables and the objective is studied to find out the key variables that most affect the objective. Response surface analysis is also performed to get the nonlinear relationship between the key design variables and the objective with the Kriging algorithm. Finally, after the optimization, an aerodynamic performance comparison between the optimal shape and the original shape reveals that the original shape of CRH3 high speed train owns a very stable aerodynamic performance and can be trustingly used in industry.
