外形隐身设计空间分析及气动隐身设计方法

Shape stealth is the primary factor determining the stealth performance of an aircraft. In the shape design of modern military aircraft, both aerodynamic performance and stealth performance need to be comprehensively considered. Aerodynamic stealth optimization is a complex multimodal problem. Given the high computational cost of global optimization and the tendency of gradient optimization to fall into local optima, an optimal design method combining global multimodal optimization for airfoils and gradient optimization for layouts is proposed. To address the insufficient local search capability of the classical multimodal particle swarm optimization algorithm, the fitness-euclidean distance ratio ring topology local-best particle swarm optimization (FER-R3PSO) algorithm is introduced by combining the ring topology particle swarm optimization algorithm with the fitness-euclidean distance particle swarm optimization algorithm, which enhances the local search capability of the classical multimodal particle swarm optimization algorithm. To combine the multimodal search algorithm with surrogate models and reduce the computational burden of using the multimodal algorithm in engineering applications, a surrogate model point addition strategy and a peak extraction method suitable for the multimodal search algorithm are proposed. Function tests, airfoil stealth optimization, and standard aerodynamic examples are used to verify the effectiveness of the multimodal algorithm. The global/gradient coupling design for the flying wing layout is proposed, and aerodynamic stealth optimization based on the adjoint method is carried out using the three-dimensional shape obtained through global multimodal algorithm optimization of the airfoil assembly as the initial stage. The optimization results show that, compared to gradient optimization, the proposed method can achieve a shape with superior aerodynamic and stealth characteristics at a lower computational cost.