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A Genetic Algorithm based Method for the Airfoil Optimization of a Tactical Blended-Wing-Body UAV *

机译:基于遗传算法的战术混合机翼无人机的机翼优化方法*

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The current study presents the development of an in-house, low-fidelity optimization methodology, suitable for generating optimized airfoil shapes with respect to predefined goals and constrains, for Unmanned Aerial Vehicle (UAV) applications. The aim is to optimize the airfoil selection during the UAV preliminary design phase. The optimization method is that of a Genetic Algorithm (GA) and the aerodynamic analysis is conducted using the low-fidelity, panel-method-based XFOIL. To facilitate the calculations of the methodology, an in-house software is developed, based on the MATLAB environment and the optimization of the center-body airfoil profile of a tactical, fixed-wing, Blended-Wing-Body (BWB) Unmanned Aerial Vehicle (UAV) experimental prototype is solved as a case study. The results of the study indicate that the current methodology can be successfully utilized for the optimization of the BWB UAV layout by providing all-round optimized airfoils.
机译:当前的研究提出了一种内部低保真优化方法的发展,该方法适合于针对预定义的目标和约束生成优化的机翼形状,适用于无人机(UAV)应用。目的是在无人机初步设计阶段优化机翼选择。优化方法是遗传算法(GA)的优化方法,并使用基于面板方法的低保真度XFOIL进行空气动力学分析。为方便计算方法,基于MATLAB环境并优化了战术,固定翼,混合翼体(BWB)无人机的中心机翼外形,开发了内部软件(UAV)实验原型作为案例研究得到解决。研究结果表明,通过提供全方位的优化翼型,当前的方法可以成功地用于BWB无人机布局的优化。

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