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以动压、雷诺数的变化和外形的制作误差与变形作为低速反弯翼型飞翼布局小型无人机设计中的不确定性因素,以降低翼型气动特性对这些不确定因素的敏感性为目标进行稳健设计。在稳健模型的计算中,为了量化外形误差,采用改进的PARSEC方法进行翼型的参数化,为了节省计算资源和时间,采用神经网络响应面代替N-S方程求解,为了使不确定性因素对翼型性能的影响得到真实反映,采用蒙特卡罗随机实验模拟代替目标变量概率分布函数计算。对Epler186翼型的稳健设计结果表明,模型和计算方法可行且高效,可有效降低翼型对不确定因素的敏感性。
The dynamic pressure, the Reynolds number changes and the shape of the production error and deformation as the low-speed anti-bending airfoil layout of small UAV layout of Uncertainty in the design of small aerodynamic characteristics to reduce the sensitivity of these uncertainties For the goal of robust design. In the calculation of robust model, in order to quantify the shape error, an improved PARSEC method is used to parameterize the airfoil. In order to save computational resources and time, neural network response surface is used instead of NS equation to solve. In order to make the uncertainties of airfoil The effect of performance is truly reflected, and Monte-Carlo random experiment simulation is used to replace the objective variable probability distribution function calculation. The robust design results of the Epler186 airfoil show that the model and calculation method are feasible and efficient, which can effectively reduce the sensitivity of the airfoil to the uncertainties.