Narrow Results

To reduce the aerodynamic load of super high-speed elevators, in this paper, the coefficient of drag $C_d$ and the coefficient of yawing moment $C_{ym}$ of the elevator are selected as optimization objectives for the optimization of the air rectification cover (ARC) shape. The elliptic curve method was used to build the parametric model of the ARCs, six design variables were selected, and the design space of the ARC was determined. With the optimal Latin hypercube design method, the training points were selected, and the computational fluid dynamics numerical simulation was conducted to calculate the corresponding responses. Then, the relationship between the design variables and the responses was analyzed. The radial basis function (RBF) surrogate model of the relationship between the design variables and responses was constructed. Finally, the non-dominated sorting genetic algorithm-II (NSGA-II) was employed to optimize the shape of the ARC. The results show that the $C_d$ and $C_{ym}$ decrease by 16.51% and 60.92%, respectively, compared with the unoptimized ARC, indicating that the ARC designed in this paper is optimized and can effectively reduce the aerodynamic load. Furthermore, among all the design variables, the bluntness of the ARC in the $X$-direction has the most significant effect on the aerodynamic load, and the height of the ARC ($h_1$ and $h_2$) has the second most significant effect on the aerodynamic load of elevators.