Colloquium: Damy Zilver (FPT)

24 september 2024 15:45 - Locatie: Lecture Room C, FACULTY OF AEROSPACE ENGINEERING, KLUYVERWEG 1, DELFT | Zet in mijn agenda

Optimal UAV Approaches in Wind-Affected Maritime Operations

A rotary-wing aircraft, or helicopter, is crucial for maritime operations due to its Vertical Take-Off and Landing (VTOL) capabilities, making it essential for small-deck Naval ships. Helicopters serve multiple roles, enhancing the Royal Netherlands Navy's (RNLN) missions. However, the rise of Unmanned Aerial Vehicles (UAVs) in the past decade has introduced a cheaper, expendable, and more efficient alternative for certain operations, as UAVs require no pilot and can operate continuously. UAVs are ideal for tasks related to improving situational awareness, thereby increasing mission effectiveness, reducing pilot risk, and lowering fuel consumption. The RNLN aims to utilize  UAVsalongside crewed helicopters on new ships to maximize operational efficiency. Both helicopters and UAVs follow three mission phases: launch, mission, and recovery, with the recovery phase being the most challenging. During the recovery phase, a crewed helicopter approaches the sailing vessel in a standardized way for which operational limits are established. These limits are essential for rough weather situations and are determined through many flight tests, which is a time-consuming, expensive and hazardous task. In addition, these operational limits only apply to a standardized approach manoeuvre. No approaches for UAVs are prescribed yet, making it difficult to determine such limits, but opens the possibility to standardize newly optimal UAV-ship approaches for which operational limits can be established. Moreover, the ship needs to manoeuvre to obtain optimal wind conditions for an approaching helicopter, which is not desired for UAVs. This means that UAVs should be able to approach and land on the ship in any wind condition. This study investigated the effect of wind on optimized UAV-ship approaches, which can be used to aid and standardize maritime UAV-ship approaches. For this objective, a trajectory optimization framework was created that combined helicopter dynamics and performance, a ship, three wind models of increasing levels of accuracy and a solver to find optimal wind-affected approaches. Trajectories were optimized to be smooth and fast because this is most important for operational purposes. Experiments involved several wind directions, wind speeds and helicopter starting positions, affected by three wind models. This work shows that the created framework functions properly and can be used in a variety of situations. The optimized trajectories were evaluated by the Longest Common SubSequence (LCSS) similarity measure to investigate the effect of both wind direction, speed and model fidelity. With an output between 0 and 1, the LCSS algorithm provided intuitive results and clear trends. A conclusion is that the helicopter wants to exploit the wind as much as possible. It diverts its path to acquire a higher ground speed at the start and a stronger headwind to decelerate at the end of the approach. When introducing a wind gradient, it was observed that the helicopter adjusted its vertical manoeuvre with the same objective. In some wind cases, constraint limits were reached or violated, marking preliminary operational limits. Results were also interpreted with a different perspective to find the best starting positions for the helicopter to approach the vessel in a certain wind condition. These results showed a variety of optimal starting locations, based on the total objective function value, total energy consumption and by distance normalized quantities. Wind model fidelity did not influence this outcome significantly, but it showed that it is important to estimate performance parameters with higher-fidelity models for increased wind speeds. This could also be seen from the downdraft behind the hangar; while the optimized approaches did not deviate geometrically, performance indicators such as the power required were affected significantly.

Supervisor: Dr. C. Varriale