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The first cross-industry guidelines for the implementation of structural health monitoring for aerospace applications have been created as a SAE International Aerospace Recommended Practices document: SAE ARP 6461 ‘Guidelines for Implementation of Structural Health Monitoring on Fixed Wing Aircraft’ [1]. These guidelines have brought together manufacturers, operators / users, systems integrators, regulators, technology providers and researchers to produce information on the integration of SHM into aircraft maintenance procedures, generic requirements and advice on validation, verification and airworthiness. The take-up of SHM in the aerospace industry has been slow, in part due to the lack of accepted industry practices surrounding not just the technology itself (sensors and sensor systems) but also the associated issues arising from the introduction of new methods into aircraft maintenance.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

Global aviation is growing exponentially and there is a great emphasis on trajectory optimization to reduce the overall environmental impact caused by aircraft. Many optimization techniques exist and are being studied for this purpose. The CLEAN SKY Joint Technology Initiative for aeronautics and Air transport, a European research activity run under the Seventh Framework program, is a collaborative initiative involving industry, research organizations and academia to introduce novel technologies to improve the environmental impact of aviation. As part of the overall research activities, “green” aircraft trajectories are addressed in the Systems for Green Operations (SGO) Integrated Technology Demonstrator. This paper studies the impact of large commercial aircraft trajectories optimized for different objectives applied to the on board systems.

The aviation sector has played a significant role in shaping the world into what it is today. The rapid growth of global economies and the corresponding sharp rise in the number of people now wanting to travel on business and for pleasure, has largely been responsible for the development of this industry. With a predicted rise in Revenue Passenger Kilometers (RPK) by over 150% in the next 20 years, the industry will correspondingly be a significant contributor to environmental emissions. Under such circumstances optimizing aircraft trajectories for lowered emissions will play a critical role amongst various other measures, in mitigating the probable environmental effects of increased air traffic. Aircraft trajectory optimization using evolutionary algorithms is a novel field and preliminary studies have indicated that a reduction in emissions is possible when set as objectives.

The installation of essential systems into aircraft wings involves numerous labour-intensive processes. Many human operators are required to perform complex manual tasks over long periods of time in very challenging physical positions due to the limited access and confined space. This level of human activity in poor ergonomic conditions directly impacts on speed and quality of production but also, in the longer term, can cause costly human resource problems from operators' cumulative development of musculoskeletal injuries. These problems are exacerbated in areas of the wing which house multiple systems components because the volume of manual work and number of operators is higher but the available space is reduced. To improve the efficiency of manual work processes which cannot yet be automated we therefore need to consider how we might redesign systems installations in the enclosed wing environment to better enable operator access and reduce production time.

This paper describes the impact of noise on the civil aircraft design process. The challenge to design ‘silent’ aircraft is the development of efficient airframe-engine technologies, for which integration is essential to produce an optimum aircraft, otherwise penalties such as higher fuel consumption, and, or noise are a concern. A description of work completed by Cranfield University will cover design methodologies used for a Broad delta airframe concept, with reference to future studies into alternate concepts. Engine cycle designs for ultra-high bypass ratio, constant volume combustor, and recuperated propulsion cycles are described, with a discussion of integration challenges within the airframe.

The vehicle dynamics control systems are traditionally based upon utilizing wheel brakes as actuators. However, there has been recently strong interest in the automotive industry for introduction of other vehicle dynamics actuators, in order to improve the overall vehicle stability, responsiveness, and agility features. This paper considers various actuators such as active rear and central differentials and active front and rear steering, and proposes design of related yaw rate control systems. Different control subsystems such as reference model, feedback and feedforward control, allocation algorithm, and time-varying controller limit are discussed. The designed control systems are verified and compared by computer simulation for double lane change and slalom maneuvers.

Significant effort has been applied to the introduction of automation for the structural assembly of aircraft. However, the equipping of the aircraft with internal services such as hydraulics, fuel, bleed-air and electrics and the attachment of movables such as ailerons and flaps remains almost exclusively manual and little research has been directed towards it. The problem is that the process requires lengthy assembly methods and there are many complex tasks which require high levels of dexterity and judgement from human operators. The parts used are prone to tolerance stack-ups, the tolerance for mating parts is extremely tight (sub-millimetre) and access is very poor. All of these make the application of conventional automation almost impossible. A possible solution is flexible metrology assisted collaborative assembly. This aims to optimise the assembly processes by using a robot to position the parts whilst an operator performs the fixing process.

In today's aircraft the diagnostic and prognostic systems play a crucial part in aircraft safety while reducing the operating and maintenance costs. Aircraft are very complex in their design and require consistent monitoring of systems to establish the overall vehicle health status. Most diagnostic systems utilize advanced algorithms (e.g. Bayesian belief networks or neural networks) which usually operate at system or sub-system level. The sub-system reasoners collect the input from components and sensors to process the data and provide the diagnostic/detection results to the flight advisory unit. Several sources of information must be taken into account when assessing the vehicle health, to accurately identify the health state in real time. These sources of information are independent system-level diagnostics that do not exchange any information/data with the surrounding systems.

Unmanned Aerial Vehicles (UAVs) provide the ability to perform a variety of experimental tests of systems and unproven research technologies, including new autopilot systems and obstacle avoidance capabilities, without risking the lives of human pilots. This paper describes the activities of design, optimization, and flight operations of a UAV conceived at Clarkson University (USA) and equipped to perform wind speed measurements to support wind farmsite planning. The UAV design has been assisted and validated by the use of an automatic virtual environment for the assisted design of civil UAVs. This tool can be used as a “computing machine” for civil UAVs. The operator inputs the mission profile and other generic parameters and data about performance, aerodynamics, and weight breakdown are extracted. A mathematical model of the UAV for flight simulation and its dynamic computations, along with automatic drawing is also produced.

Scaled models are often used to check the aerodynamic performance of full scale aircraft and airship concepts, which have gone through a conceptual and preliminary design process. Results from these tests can be quite useful to improve the design of unconventional airships whose aerodynamics might be quite different from classical configurations. Once the airship geometry has been defined, testing is required to acquire aerodynamic data necessary to implement the mathematical model of the airship needed by the flight control system to develop full autonomous capabilities. Rapid prototyping has the great potential of playing a beneficial role in unconventional autonomous airship design similarly to the success obtained in the design process of conventional aircrafts.

Added masses computation is a crucial aspect to be considered when the density of a body moving in a fluid is comparable to the density of the fluid displaced: added mass can be defined as the inertia added to a system because an accelerating or decelerating body displaces some volume of neighboring fluid as it moves through it. The motion of vehicles like airships and ships can be addressed only by keeping into account the effect of added masses, while in case of aircrafts and helicopters this contribution is usually neglected. Lighter Than Air flight simulation, unmanned airships flight control system, airships flight dynamics are typical applications in which added masses are fundamental to achieve an effective and realistic modeling. A panel based method using the mesh of an airship external shape is developed to account for the added massed.

This paper presents a 14 degrees of freedom vehicle model. Despite numerous software are nowadays commercially available, the model presented in this paper has been built starting from a blank sheet because the goal of the authors was to realize a model suitable for real-time simulation, compatible with the computational power of typical electronic control units, for on-board applications. In order to achieve this objective a complete vehicle dynamics simulation model has been developed in Matlab/Simulink environment: having a complete knowledge of the model's structure, it is possible to adapt its complexity to the computational power of the hardware used to run the simulation, a crucial feature to achieve real-time execution in actual ECUs.

UAS (Unmanned aircraft system), widely known to the general public as drones, are comprised of two major system elements: an Unmanned Aircraft (UA) and a Ground Control Station (GCS). UAS have a high mishap rate when compared to manned aircraft. This high mishap rate is one of several barriers to the acceptance of UAS for more widespread usage. Better awareness of the UA real time as well as long term health situation may allow timely condition based maintenance. Vehicle health and usage are two parts of the same solution to improve vehicle safety and lifecycle costs. These can be worked on through the use of two related aircraft management methods, these are: IVHM (Integrated Vehicle Health Management) which combines diagnosis and prognosis methods to help manage aircraft health and maintenance, and FOQA (Flight Operations Quality Assurance) systems which are mainly used to assist in pilot skill quality assurance.

This paper describes the design and development of a virtual environment conceived to support flight operations of an Unmanned Air Vehicle (UAV) used for wind mapping in the proximity of existing or planned wind farms. The virtual environment can be used in pre-flight briefings aiming to define a trajectory from a list of waypoints, to change and eventually re-plan the mission in case of intersection with no fly zones, to simulate the mission, and to preview images/videos taken from the UAV on-board cameras. During flight, the tool can be used to compute the wind speed along the trajectory by analyzing the data streaming from the UAV. The integration of Augmented Reality (AR) techniques in the flight environment provides assistance in remotely piloted landings, and allows visualizing flight and environmental information that are critical to the mission.

Co-production of aircraft is resulting in demands for higher standards of manufacturing quality to ensure that parts and sub-assemblies from different companies and countries are compatible and interchangeable. As a result the existing method of building aerostructure using large numbers of dedicated manufacturing jigs and assembly tools, is now seen as being commercially undesirable, and technologically flawed. This paper considers an alternative, potentially more cost-effective, approach that embraces digital design, manufacturing, and inspection techniques, and in which reference and tooling features are incorporated into the geometry of the component parts. Within the aerospace industry this technology is known as ‘Flyaway Tooling’.

The motion of a vehicle along a desired path is possible due to steering action of the driver. Hence, vehicle dynamics and control simulations should take into consideration the action of the driver. This work presents a preview based vehicle steering controller using Neural Networks which can be used in the vehicle lateral dynamics simulations. The training data for the Neural Network is being obtained using a steering controller from the existing literature and its gains are determined using Optimization. Three different architectures are being designed and conclusions are presented. These Neural Network models are validated by testing against real track data.

In all Ducati L-twins the crankshaft supports are rolling bearings. Due to the higher performance, compactness and lightness, the service life of the crankcase is becoming shorter and in future can become critical in the Ducati 999, the most powerful engine of the Borgo Panigale company. The engine block sidewalls must be strengthened in order to improve the reliability of the component. This can be done by reducing the size of the main bearing housings by the adoption of the plain bearings which have smaller radial dimensions. The stress field of the Ducati 999 crankcase in the two different configurations is calculated by means of the finite element method, applying the engine load in the critical conditions.

In the current literature, the research studies on the trajectory tracking control and stability control strategy for autonomous vehicles in limited condition mostly focus on the yaw plane control, but few of the studies have considered the combined control performance of trajectory tracking, yaw and roll stability, and the roll stability is critical under the extreme cornering condition for autonomous vehicles. Aiming at the above shortages, this study designs the model predictive control (MPC) strategy for the autonomous vehicles under the limited handling condition, which integrates the front and rear wheel active steering control, four-wheel independent drive and braking control and active suspension control to comprehensively improve the trajectory tracking accuracy, yaw plane stability and roll plane stability of the vehicle under the extreme condition.

Transient force and surface pressure data has been measured on a range of simple geometric shapes in order to gain an understanding of the complex time dependent and separated flow around a vehicle when subjected to a crosswind. The experiments were carried out using the Cranfield University model crosswind facility. It is found that the leeward face is the dominant area of transient activity. Maximum and minimum peak yawing moments at gust entry and exit are compared