A novel statistical model is presented to quantify situation awareness in the operation of small civilian Unmanned Aircraft Systems (UAS). Today, the vast majority of small Unmanned Aircraft Systems (UAS) operation takes place under Visual Line of Sight (VLOS) of a human operator, who is wholly responsible for the safety of the flight. As operation begins to move to Beyond Visual Line of Sight (BVLOS), it is likely that this responsibility will become shared between operator and the increasingly autonomous UAS itself. Before we seek to quantify the safety of such a system, it is beneficial to analyse the safety of existing Visual Line of Sight (VLOS) operations to provide a target level of safety. Prior to considering any on-board decision making, it is essential to ensure that the artificial situation awareness system of a UAS in Beyond Visual Line of Sight (BVLOS) is at least as good as awareness of a human operator. The paper provides a probabilistic theory and model for the high-level abstractions of situation awareness to guide future assessment of BVLOS operations.

An intelligent decision-making method was proposed for airport bird-repelling based on a Support Vector Machine (SVM) and bird-strike risk assessment. The bird-strike risk assessment model is established with two exponential functions to separate the risk levels, while the SVM method includes two steps of training and testing. After the risk assessment, the Bird-Repelling Strategy Classification Model (BRSCM) was trained based on the expert knowledge and large amount of historical bird information collected by the airport linkage system for bird detection, surveillance and repelling. Then, in the testing step, the BRSCM was continuously optimised according to the real-time intelligent bird-repelling strategy results. Through several bird-repelling examples of a certain airport, it is demonstrated that the decision accuracy of BRSCM is relatively high, and it could solve new problems by self-correction. The proposed method achieved the optimised operation of multiple bird-repelling devices against real-time bird information with great improvement of bird-repelling effects, overcoming the tolerance of birds to the bird-repelling devices due to their long-term repeated operation.

Carbon fibres with high tensile strength are being increasingly utilised in the manufacture of advanced composite aerostructures. A Modified Compact Tension (MCT) specimen is often deployed to measure the longitudinal intralaminar fracture toughness but a high tensile strength often leads to premature damage away from the crack tip. We present an approach whereby the MCT specimen is supported by external fixtures to prevent premature damage. In addition, we have developed a novel measurement technique, based on the fibre failure strain and C-scanning, to determine the crack length in the presence of surface sublaminate delamination which masks the crack tip location. A set of cross-ply specimens, with a ((90/0)s)4 layup, were manufactured from an IMS60/epoxy composite system Two different data reduction schemes, compliance calibration and the area method, are used to determine the fibre-dominated initiation and propagation intralaminar fracture toughness values. Propagation values of fracture toughness were measured at 774.9 ± 5.2% kJ/m2 and 768.5 ± 4.1% kJ/m2, when using the compliance calibration method and the area method, respectively. Scanning Electron Microscopy (SEM) is carried out on the fracture surface to obtain insight into the damage mechanism of high-tensile-strength fibre-reinforced unidirectional composites. The measured tensile fracture toughness value is used in a fully validated computational model to simulate the physical test.

This paper investigates the synergies and trade-offs between passive aeroelastic tailoring and adaptive aeroelastic deformation of a transport composite wing for fuel burn minimisation. This goal is achieved by optimising thickness and stiffness distributions of constitutive laminates, jig-twist shape and distributed control surface deflections through different segments of a nominal “cruise-climb” mission. Enhanced aerostructural efficiency is sought both passively and adaptively as a means of aerodynamic load redistribution, which, in turn, is used for manoeuvre load relief and minimum drag dissipation. Passive shape adaptation is obtained by embedding shear-extension and bend-twist couplings in the laminated wing skins. Adaptive camber changes are provided via full-span trailing-edge flaps. Optimised design solutions are found using a bi-level approach that integrates gradient-based and particle swarm optimisations in order to tailor structural properties at rib-bay level and retrieve blended stacking sequences. Performance benefits from the combination of passive aeroelastic tailoring with adaptive control devices are benchmarked in terms of fuel burn and a payload-range efficiency. It is shown that the aeroservoelastically tailored composite design allows for significant weight and fuel burn improvements when compared to a similar all-metallic wing. Additionally, the trailing-edge flap augmentation can extend the aircraft performance envelope and improve the overall cruise span efficiency to nearly optimal lift distributions.

The next generation of civil large aero-engines will employ greater bypass ratios compared with contemporary architectures. This results in higher exchange rates between exhaust performance and specific fuel consumption (SFC). Concurrently, the aerodynamic design of the exhaust is expected to play a key role in the success of future turbofans. This paper presents the development of a computational framework for the aerodynamic design of separate-jet exhaust systems for civil aero-engines. A mathematical approach is synthesised based on class-shape transformation (CST) functions for the parametric geometry definition of gas-turbine exhaust components such as annular ducts and nozzles. This geometry formulation is coupled with an automated viscous and compressible flow solution method and a cost-effective design space exploration (DSE) approach. The framework is deployed to optimise the performance of a separate-jet exhaust for very-high-bypass ratio (VHBR) turbofan engine. The optimisations carried out suggest the potential to increase the engine’s net propulsive force compared with a baseline architecture, through optimum exhaust re-design. The proposed method is able to identify and alleviate adverse flow-features that may deteriorate the aerodynamic behaviour of the exhaust system.

Optimisation of aircraft ground operations to reduce airport emissions can reduce resultant local air quality impacts. Single engine taxiing (SET), where only half of the installed number of engines are used for the majority of the taxi duration, offers the opportunity to reduce fuel consumption, and emissions of NOX, CO and HC. Using 3510 flight data records, this paper develops a model for SET operations and presents a case study of London Heathrow, where we show that SET is regularly implemented during taxi-in. The model predicts fuel consumption and pollutant emissions with greater accuracy than previous studies that used simplistic assumptions. Without SET during taxi-in, fuel consumption and pollutant emissions would increase by up to 50%. Reducing the time before SET is initiated to the 25th percentile of recorded values would reduce fuel consumption and pollutant emissions by 7–14%, respectively, relative to current operations. Future research should investigate the practicalities of reducing the time before SET initialisation so that additional benefits of reduced fuel loadings, which would decrease fuel consumption across the whole flight, can be achieved.