Aerodynamic flow modeling for helicopters landing on ships

飞机飞行模拟是一个久负盛名的领域，为社会提供了极高的性价比。飞机和直升机的飞行模拟器可以有效地培训飞行员(时间和成本)，同时降低失去飞机或更糟糕的飞行员的风险。该项目旨在提高直升机降落在舰船上的实时飞行仿真程序中所使用的空气动力学模型的逼真度。模型将是混合保真的：无粘流动将通过涡格子方法模拟，而粘性流动将通过非定常雷诺平均纳维斯托克斯(URANS)方法模拟。特别是，重点将放在周期性运动的转子流动建模上。将通过协作的方法来研究可压缩性、跨音速流动条件、边界层和尖端涡流的影响，以及船舶尾迹的影响。蒙特理工学院的Laurendeau教授的团队将通过执行器盘边界条件检查中央处理单元(CPU)/图形处理单元(GPU)上的时间精确无粘性模型以及转子流动模型，而McGill大学的Nadarajah教授的团队将专注于周期性粘性流动模型。CAE将使用商业3D流动解算器检查船舶尾迹模型，以提供有关船舶尾迹的信息。**该项目将为2名理学硕士、2名博士和1名博士后提供实时空气动力流动模型方面的培训。这一结果将提高CAE的直升机飞行模拟能力，并提供可用于风能(风电场)和发动机(涡轮风扇和涡轮螺旋桨)领域的新算法。例如，风力涡轮机行业可以使用这些算法来预测风力发电场的尾流效应。造船业需要螺旋桨模型。航空航天工业可以从涡轮螺旋桨/涡轮喷气发动机的NLFD方法中受益。新创建的无人机市场在受到监管后，将需要检查尾流效应。最后，这项技术可以服务于民用和军事部门，以实现更安全、更有效的空中行动。

Flight simulation of aircraft is a well-established field providing excellent value/price ratio to the community. Flight simulators for airplanes and helicopters allow efficient pilot training (time and costs) while reducing risks of losing an aircraft or worse, pilots. This project aims at increasing the fidelity of aerodynamic models used in real-time flight simulation packages for helicopter landing on ships. The models will be of mixed-fidelity: the inviscid flow will be modeled via Vortex Lattice methods, while viscous flows will be modeled via Unsteady Reynolds-averaged Navier-Stokes (URANS) methods. In particular, emphasis will be placed on rotor flow modeling with periodic motions. The effects of compressibility, transonic flow conditions, boundary-layers, and tip vortex will be examined, as well as the effects of ship wakes by a collaborative approach. Prof. Laurendeau's team at Polytechnique Montréal will examine the time-accurate inviscid models on Central Processing Units (CPU)/Graphics Processing Units (GPU) and on rotor flow models via the actuator disk boundary conditions while Prof. Nadarajah's team at McGill University will concentrate on periodic viscous flow models. CAE will examine the ship wake model with a commercial 3D flow solver to provide information on ship wakes.**The project will provide training for 2 M.sc., 2 Ph.D. and 1 Post-Doctoral student in the area of real-time aerodynamic flow models. The results will increase CAE's flight simulation capabilities for helicopter flight, as well as provide novel algorithms that can be used in the field of wind-energy (wind-farms) and engines (turbo-fan and turbo-propellers). For instance, the wind-turbine industry can use the algorithms for the prediction of wind-farm wake effects. The ship industry requires propellers models. The aerospace industry could benefit from the NLFD approach for turbopropellers/turbo-jet engines. The newly created drone market, when regulated, will need to examine wake effects. Finally, the technology can serve the civil as well as the military sectors for more secure and efficient air operations.**************