Bio-inspired flow control studies under gust and turbulence effect for next-generation Urban Air Mobility aircraft.

该项目旨在利用鸟类对湍流区的自动反应能力。通过应用它们对这些扰动的反应，这些适应可以实施到城市空中机动性(UAM)飞机上，这些飞机在高度动荡的地区的城市运营。为了开始这个项目，我们首先需要了解鸟类，在我们的案例中，扑翼飞行的人是如何对受控的阵风做出反应的。通过使用斯旺西研究生设计和生产的设备，可以将测量到的阵风发送给鸽子。所讨论的阵风是非定常流动的区域，这将人为地增加鸟类的攻角。这将迫使鸟进行操纵，重新进入稳定、无加速的水平飞行。这一反应将使用动作捕捉软件以及慢动作视觉摄像机进行测量，所有这些都将以多种不同的组合进行收集，以便捕捉拍打飞行的人用来纠正自身的机制。所有的数据都将经过后期处理，特别是动作捕捉，以获得一个数值，以便了解鸽子的反应以及将来复制原型时的比较数据。一旦我们了解了鸽子在飞行中使用的机制，我们可能会想要运行CFD模型，在那里我们可以测试原型，这将试图重现鸽子已经取得的成就。这将降低成本，因为要建造的原型更少，而且它们可能会有更高的成功率。然而，根据模拟的复杂性，只咨询理论方面并在湾区制造更多待测试的原型可能会更省时。然后我们想把原型放在鸽子所处的相同条件下。这将证明原型是否具有相同的抗阵风能力，随着海湾风洞中提供更快的速度，我们将能够看到，从鸽子那里学到的抗阵风能力在什么程度上适用。

This project aims to take advantage of the automatic response birds have inflight to turbulent flow regions. By applying how they respond to these perturbation, these adaptations can be implemented to urban air mobility (UAM) aircraft, which operate in cities which are highly turbulent regions. To begin this project we first need to understand how birds, and in our case flapping flyers, react to controlled gusts. By using equipment designed and produced by Swansea postgraduates, measured gust can be sent towards Pigeons. The gusts in question are regions of unsteady flow, which will artificially increase the birds angle of attack. This will force the bird to manoeuvre to get back into steady, unaccelerating level flight. This response will be measured using motion capture software's as well as slow motion visual cameras and all will be collected in a multitude of different combinations in order to capture the mechanisms flapping flyers use to correct themselves. All of the data will be post processed, especially motion capture, to gain a numerical values in order to understand the response of the Pigeons as well as comparative data when, in the future, protypes replicating will have statistics to compare with. Once we understand what mechanisms the Pigeons are using for flight we may want to run CFD models where we can test prototypes which will try and recreate what the Pigeons have already achieved. This would reduce cost as less prototypes are going to built and they will likely have a higher success rate. However, depending on the complexity of the simulations, it maybe more time efficient to only consult the theoretical aspects and manufacture more prototypes to be tested at Bay campus. We then want to put prototypes through the same conditions the Pigeons were under. This will prove that the prototypes share the same gust rejection or not, and with faster speeds available in the wind tunnel at Bay, we will be able to see, to what extent the gust rejection learnt from the pigeons is applicable to.