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New methodology for calculating flight parameters with neural network - EGD method

机译:用神经网络计算飞行参数的新方法-EGD方法

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The determination of flight parameters such as pressure distributions and aerodynamic coefficients (lift, drag and moment) from the known parameters (angle of attack, Mach number...) in real time is still not achievable easily by methods of numerical analysis in aerodynamics and aeroelasticity domains. For this reason, we propose a flight parameters control system. This approach is based on new optimization methodologies with neural networks (NN) and extended great deluge (EGD). The validation of this method is realized by experimental tests using a model installed on wind tunnel to determine the pressure distribution. For lift, drag and moment coefficient, the results of our approach are compared to the XFoil results for different angles of attack. The main purpose of this control system is to improve the aircraft aerodynamic performance.
机译:通过空气动力学和空气动力学的数值分析方法仍然难以轻易地从已知参数(迎角,马赫数...)实时确定飞行参数,例如压力分布和空气动力学系数(升力,阻力和力矩)。气动弹性域。因此,我们提出了一种飞行参数控制系统。该方法基于具有神经网络(NN)和扩展大洪水(EGD)的新优化方法。通过使用安装在风洞中的模型确定压力分布的实验测试来实现此方法的有效性。对于升力,阻力和力矩系数,将我们的方法的结果与针对不同迎角的XFoil结果进行比较。该控制系统的主要目的是改善飞机的空气动力学性能。

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