高效粒子群算法研究及飞翼无人机气动隐身优化设计

针对飞翼布局无人机气动隐身多目标优化设计问题,以无人机翼面为设计对象,开展气动、隐身多目标优化设计研究。采用FFD方法实现飞翼布局的参数化表达；分别采用基于雷诺平均N-S方程的计算流体力学方法(CFD)及大面元物理光学法(LEPO)配合一致性几何绕射理论(UTD)计算边缘绕射场的RCS分析方法计算飞翼布局无人机的气动、隐身性能；选择结合基于动态超体积期望改善(EHVI)加点的动态Kriging代理模型与ASMOPSO算法的高效多目标粒子群算法对飞翼布局无人机进行综合寻优设计研究。在较少的调用真实目标函数的情况下,获得了比较优秀的Pareto前沿,通过对所选解的分析比较可知优化后的飞翼布局无人机在气动及隐身方面均优于原始构型。

Aerodynamic and stealth integrated design of Flywing UAV by Efficient multi-objective particle swarm optimization

To deal with the problem of aerodynamic and stealth integrated optimization of flywing UAV,A multi-objective optimization study on aerodynamic and stealth of the flywing UAV is carried out which based on the deformation of surface. The FFD parametric method is used to parameterize the wing surface; CFD calculation based on RANS equations is used to analyze the aerodynamic performance of the flywing UAV, large element physical optical method and uniform theory of diffraction are used to calculate RCS of the flywing UAV; And ASMOPSO algorithm with the Kriging surrogate model which based on the expect hyper-volume improvement infill criterion is adopted for integrated optimization design. The results of flywing UAV aerodynamic and stealth integrated optimization exhibit considerable improvement.