Aerofoil Design for Unmanned High-Altitude Aft-Swept Flying Wings

ABSTRACT In this paper, 12 new aerofoils with varying thicknesses for an aft-swept flying wing unmanned air vehicle have been designed using a MATLAB tool which has been developed in-house. The tool consists of 2 parts in addition to the aerodynamic solver XFOIL. The first part generates the aerofoil section geometry using a combination of PARSEC and Bezier-curve parameterisation functions. PARSEC parametrisation has been used to represent the camber line while the Bezier-curve has been used to select the thickness distribution. This combination is quite efficient in using an optimisation search process because of the capability to define a range of design variables that can quickly generate a suitable aerofoil. The second part contains the optimisation code using a genetic algorithm. The primary target here was to design a number of aerofoils with low pitching moment, suitable for an aft-swept flying wing configuration operating at low Reynolds number in the range of about 0.5 × 106. Three optimisation targets were set to achieve maximum aerodynamic performance characteristics. Each individual target was run separately to design several aerofoils of different thicknesses that meet the target criteria. According to the set of result obtained so far, the initial observation of the aerodynamic performance of the newly designed aerofoils is that the lift/drag ratio in general is higher than that of the existing ones used in many current-generation high-altitude long-endurance aircraft. Another observation is that increasing the maximum thickness of the aerofoil leads to a decrease in the maximum lift/drag ratio. In addition, as expected, this ratio sharply drops after the maximum value of some of these aerofoils.摘要 本文针对后掠飞翼式无人机（unmanned air vehicle），采用自研MATLAB工具设计了12款不同厚度的新型翼型（aerofoil）。该工具除气动求解器XFOIL外，包含两个功能模块。第一模块结合PARSEC与贝塞尔曲线（Bezier-curve）参数化函数生成翼型截面几何：其中PARSEC参数化方法用于描述翼型中弧线（camber line），贝塞尔曲线用于确定翼型厚度分布（thickness distribution）。该组合方式可定义一系列设计变量，快速生成适配性翼型，在优化搜索流程中具备较高效率。第二模块搭载基于遗传算法（genetic algorithm）的优化代码。本次设计的核心目标为生成多款低俯仰力矩翼型，适配工作在约0.5×10⁶雷诺数（Reynolds number）下的后掠飞翼布局无人机。本次设置了三项优化目标以最大化气动性能指标。针对每项优化目标独立开展设计流程，生成多款满足目标准则的不同厚度翼型。基于目前已获取的研究结果，对新型翼型气动性能的初步观测显示：其升阻比（lift/drag ratio）整体优于当前多款现役高空长航时飞行器所采用的翼型。另一项观测结果表明，翼型最大厚度提升会使最大升阻比下降。此外，如预期一致，部分翼型在达到最大升阻比后，升阻比会出现急剧下滑。