Method and system for determining helicopter rotor airfoil

    公开(公告)号:US11423201B2

    公开(公告)日:2022-08-23

    申请号:US17312336

    申请日:2020-08-07

    摘要: The present disclosure provides a method and system for determining a helicopter rotor airfoil. The method includes: randomly generating a sample point by using a Latin hypercube sampling (LHS) method (S1); determining characterization equations of upper and lower airfoil surfaces of an airfoil based on the airfoil sample point by using a class shape transformation (CST) method (S2); performing dynamic characteristic simulation on the airfoil according to the characterization equations of the upper and lower airfoil surfaces by using a computational fluid dynamics (CFD) method, to obtain a flow field characteristic of the airfoil (S3); establishing a mapping relationship between the sample point and the flow field characteristic by using a Kriging model, and training the mapping relationship by using a maximum likelihood estimation method and an expected improvement (EI) criterion, to obtain a trained mapping relationship (S4); determining an optimal sample point based on the trained mapping relationship by using Non-dominated Sorting Genetic Algorithm II (NSGA-II) (S5); and determining a rotor airfoil based on the optimal sample point (S6). The method performs optimized design on aerodynamic characteristics of the airfoil in a state with a changing incoming flow and a changing angle of attack, and can effectively alleviate dynamic stall in this state.

    METHOD AND SYSTEM FOR DETERMINING HELICOPTER ROTOR AIRFOIL

    公开(公告)号:US20220033062A1

    公开(公告)日:2022-02-03

    申请号:US17312336

    申请日:2020-08-07

    摘要: The present disclosure provides a method and system for determining a helicopter rotor airfoil. The method includes: randomly generating a sample point by using a Latin hypercube sampling (LHS) method (S1); determining characterization equations of upper and lower airfoil surfaces of an airfoil based on the airfoil sample point by using a class shape transformation (CST) method (S2); performing dynamic characteristic simulation on the airfoil according to the characterization equations of the upper and lower airfoil surfaces by using a computational fluid dynamics (CFD) method, to obtain a flow field characteristic of the airfoil (S3); establishing a mapping relationship between the sample point and the flow field characteristic by using a Kriging model, and training the mapping relationship by using a maximum likelihood estimation method and an expected improvement (EI) criterion, to obtain a trained mapping relationship (S4); determining an optimal sample point based on the trained mapping relationship by using Non-dominated Sorting Genetic Algorithm II (NSGA-II) (S5); and determining a rotor airfoil based on the optimal sample point (S6). The method performs optimized design on aerodynamic characteristics of the airfoil in a state with a changing incoming flow and a changing angle of attack, and can effectively alleviate dynamic stall in this state.