The drone market has been steadily growing over the last decades, resulting in drones becoming more and more common 1. For the majority of the time, the drones provide valuable services, from inspection work and deliveries to applications in emergencies, such as search and rescue, or rapid deliveries of medical supplies. Unfortunately, because drones are available to everyone, misuse cannot be fully prevented. They can cause significant disruptions to aviation, violate privacy, or transport illegal substances, leading to financial losses, or more serious consequences. A notable incident, that caused the delay of close to 1,000 flights affecting approximately 140,000 passengers, took place in 2018 at London Gatwick Airport, where 2 drones caused the airport to shut down for over 24 hours [1]. Additionally, it has been reported by Dubai International Airport, that the estimated costs of halting airport operations due to drones resulted in losses of close to $100,000 per minute of downtime2. To counteract these hazardous situations, current anti-drone methods on the market include drone guns, quadcopters using catching systems, and radio frequency jamming systems. However, all of these methods come with their disadvantages. They either involve human interaction, have high operational costs, or cannot intercept quickly over a large area, leaving a large gap in the market for an efficient anti-drone system. The Air-Guard drone introduced in this report aims to fill this market gap, by providing a quick response time to a threat, while not compromising on neutralizing capabilities. It is a fixed-wing drone capable of autonomous visual tracking and catching unlicensed drones via a shooting net mechanism integrated with a parachute. Compared to multi-rotor drones, the Air-Guard drone concept has a longer range and higher efficiency, allowing it to be readily in the air until an unlicensed drone is detected. This is achieved thanks to its unique design inspired by bird morphology. Birds can actively morph their wings and tail surfaces to actively alter their aspect ratio, wing loading, and stability to achieve the most efficient flight configuration over a wide variety of flight profiles. Similarly, the Air-Guard drone morphs its wing and tail such that the drone can be stable while loitering, to then transition into high-g maneuvers in under a second. This allows the drone to more closely follow unlicensed drones in restricted areas and immobilize these drones in a matter of minutes autonomously. The morphing concept of the drone uses multiple actuators and elastic tendons in combination with specially designed artificial feathers to emulate bird morphology. The design also considers previously neglected areas of bird wing anatomy and incorporates bioinspired aerodynamic surfaces to delay stall and increase the maneuverability of the drone. This report is a follow-up of the midterm report, where the general configuration of the drone was set up. It aims to describe the progress on the Air-Guard project, mostly from a technical point of view, but also economic and operational aspects are covered. The UAV design is multidisciplinary and is influenced by many disciplines related to aerospace engineering. Aerodynamics, performance, structures, stability, control, and electronics considerations were combined to make the design possible. It was an iterative process, requiring careful coordination and communication between all the different departments. The result of this work translates into the design of a dual engine, 3.5 kg drone that is capable of loitering for an hour, with a maximum speed of 48 m/s. The wing span in extended configuration is 1.34 m, with a total length of 1.05 m. To neutralize the threat, the Air-Guard chases the unlicensed drone with the help of its high maneuver ability, then fires a net equipped with a parachute from the nose to capture it. The materials used are balsa wood for the fuselage and fixed-wing, while the morphing surfaces are made of aluminum and 3D-printable Celanese VECTRA A950LCP. A great emphasis was put on the sustainability aspect of the drone, which lead to an electrically powered UAV, having a structure that is 99% recyclable.

This paper addresses the airline centred Arrival Sequencing and Scheduling problem aimed at the smart distribution of arrival delays, considering the explicit preferences from users. We consider the scenario in which actions are executed solely in the en-route phase with the available leeway present in the
current ATM system. The arrival process at the destination centre alongside equity rules such as ”First-Come, First-Served” remain untouched. A Mixed-Integer Linear Programming approach is presented in order to evaluate the fleet-wide impact of speed changes by individual aircraft in order to come to a global
(airline specific) optimum. The approach presented is evaluated using operational data in the form of a case study of a large European hub-style carrier. Case study results indicate the ability to decrease delay related cost by over 15% through the more efficient distribution of delay times between aircraft. Overall aircraft timeliness in the case study for both the controlled airline as well as competing airlines shows a slight improvement of several seconds of average delay per aircraft. In addition, a number of variations to the base model are presented, investigating a possible trade-off between model priorities.