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An accurate aeroelastic assessment of powered HALE aircraft is of paramount importance considering that their behaviour contrasts the one of conventional aircraft mainly due to the use of high aspect-ratio wings with distributed propulsion systems. This particular configuration shows strong dependency of the wing natural frequencies to the propulsion distribution and operating conditions. Numerical and experimental investigations are carried out to better understand the behaviour of flexible wings, focusing on the effect of distributed electric propulsion systems. Several configurations are investigated, including a single propulsion system using an engine pod (a weight with embedded electric motor, a propeller, and the wing-attached structure) installed at selected spanwise positions, and configurations with two and three propellers.

Avionic system developers are currently working on innovative technologies that are required in view of the rapid expansion of global air transport and growing concerns for environmental sustainability of aviation sector. Novel Communication, Navigation and Surveillance (CNS) system designs are being developed in the CNS/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) context for mission-and safety-critical applications. The introduction of dedicated software modules in Next Generation Flight Management Systems (NG-FMS), which are the primary providers of automated navigation and guidance services in manned aircraft and Remotely-Piloted Aircraft Systems (RPAS), has the potential to enable the significant advances brought in by time and trajectory based operations. High-integrity, high-reliability and all-weather services are required in the context of four dimensional Trajectory Based Operations / Intent Based Operations (TBO/IBO).

Global Navigation Satellite Systems (GNSS) can support the development of low-cost and high performance navigation and guidance architectures for Unmanned Aircraft Systems (UAS) and, in conjunction with suitable data link technologies, the provision of Automated Dependent Surveillance (ADS) functionalities for cooperative Sense-and-Avoid (SAA). In non-cooperative SAA, the adoption of GNSS can also provide the key positioning and, in some cases, attitude data (using multiple antennas) required for automated collision avoidance. A key limitation of GNSS for both cooperative (ADS) and non-cooperative applications is represented by the achievable levels of integrity. Therefore, an Avionics Based Integrity Augmentation (ABIA) solution is proposed to support the development of an Integrity-Augmented SAA (IAS) architecture suitable for both cooperative and non-cooperative scenarios.

A kinetic energy recover system (KERS) captures the kinetic energy that results when brakes are applied to a moving vehicle. The recovered energy can be stored in a flywheel or battery and used later, to help boost acceleration. KERS helps transfer what was formerly wasted energy into useful energy. In 2009, the Federation Internationale de l’Automobile (FIA) began allowing KERS to be used in Formula One (F1) competition. Still considered experimental, this technology is undergoing development in the racing world but has yet to become mainstream for production vehicles. The Introduction of this book details the theory behind the KERS concept. It describes how kinetic energy can be recovered, and the mechanical and electric systems for storing it. Flybrid systems are highlighted since they are the most popular KERS developed thus far. The KERS of two racing vehicles are profiled: the Dyson Lola LMP1 and Audi R18 e-tron Quattro.

Multi-Sensor Data Fusion (MSDF) techniques involving satellite and inertial-based sensors are widely adopted to improve the navigation solution of a number of mission- and safety-critical tasks. Such integrated Navigation and Guidance Systems (NGS) currently do not meet the required level of performance in all flight phases of small Remotely Piloted Aircraft Systems (RPAS). In this paper an innovative Square Root-Unscented Kalman Filter (SR-UKF) based NGS is presented and compared with a conventional UKF governed design. The presented system architectures adopt state-of-the-art information fusion approach based on a number of low-cost sensors including; Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Navigation (VBN) sensors.

Accurate and robust tracking of objects is of growing interest amongst the computer vision scientific community. The ability of a multi-sensor system to detect and track objects, and accurately predict their future trajectory is critical in the context of mission- and safety-critical applications. Remotely Piloted Aircraft System (RPAS) are currently not equipped to routinely access all classes of airspace since certified Detect-and-Avoid (DAA) systems are yet to be developed. Such capabilities can be achieved by incorporating both cooperative and non-cooperative DAA functions, as well as providing enhanced communications, navigation and surveillance (CNS) services. DAA is highly dependent on the performance of CNS systems for Detection, Tacking and avoiding (DTA) tasks and maneuvers.