Multi-objective and multi-constrained optimization design for a helicopter rotor airfoil

In order to overcome the drawbacks of the traditional optimization design method for a helicopter rotor airfoil, a multi-objective and multi-constrained aerodynamic optimization design method based on the genetic algorithm and the Kriging model is developed in this paper. Aerodynamic properties of the sample points are obtained by solving the Reynolds averaged Navier-Stokes equations, based on which the Kriging models of the objective functions and the state functions are created. Then, the points which have the minimum value of Kriging model and the maximum value of EI (Expected Improvement) function are searched by the genetic algorithm. The Kriging model is reconstructed by adding these new points. The above process is repeated until the global optimal solution is found. Combined with weighted sum of objective functions, the genetic algorithm is used for the helicopter rotor airfoils' multi-objective and multi-constrained optimization design. The results show that while the optimized rotor airfoil meets the constraints, the drag coefficient is reduced by 2.1% in hover flight, and the maximum lift coefficient is increased by 4.2% in the maneuvering flight, compared with the baseline airfoil of OA209 airfoil. Besides, the drag coefficient is lower than that of the baseline airfoil in the forward flight at different Mach numbers.