In this paper, the accuracy and practical capabilities of three different reduced-order models (ROMs) are explored: an enhanced implicit condensation and expansion (EnICE) model, a finite element beam model, and a finite volume beam model are compared for their capability to accurately predict the nonlinear structural response of geometrically nonlinear built-up wing structures. This work briefly outlines the different order reduction methods, highlighting the associated assumptions and computational effort. The ROMs are then used to calculate the wing deflection for different representative load cases and these results are compared with the global finite element model (GFEM) predictions when possible. Overall, the ROMs are found to be able to capture the nonlinear GFEM behaviour accurately, but differences are noticed at very large displacements and rotations due to local geometrical effects.

This study investigates a new aircraft flight trajectory optimisation method, derived from the Non-dominated Sorting Genetic Algorithm II method used for multi-objective optimisations. The new method determines, in parallel, a set of optimal flight plan solutions for a flight. Each solution is optimal (requires minimum fuel) for a Required Time of Arrival constraint from a set of candidate time constraints selected for the final waypoint of the flight section under optimisation. The set of candidate time constraints is chosen so that their bounds are contiguous, i.e. they completely cover a selected time domain. The proposed flight trajectory optimisation method may be applied in future operational paradigms, such as Trajectory-Based Operations/free flight, where aircraft do not need to follow predetermined routes. The intended application of the proposed method is to support Decision Makers in the planning phase when there is a time constraint or a preferred crossing time at the final point of the flight section under optimisation. The Decision Makers can select, from the set of optimal flight plans, the one that best fits their criteria (minimum fuel burn or observes a selected time constraint). If the Air Traffic Management system rejects the flight plan, then they can choose the next best solution from the set without having to perform another optimisation. The method applies for optimisations performed on lateral and/or vertical flight plan components. Seven proposed method variants were evaluated, and ten test runs were performed for each variant. For five variants, the worst results yielded a fuel burn less than 90kg (0.14%) over the ‘global’ optimum. The worst variant yielded a maximum of 321kg (0.56%) over the ‘global’ optimum.

The quadratic constitutive relation was proposed as an extension of minimal complexity to linear eddy-viscosity models in order to improve mean flow predictions by better estimating turbulent stress distributions. However, the successes of this modification have been relatively modest and are limited to improved calculations of flow along streamwise corners, which are influenced by weak secondary vortices. This paper revisits the quadratic constitutive relation in an attempt to explain its capabilities and deficiencies. The success in streamwise corner flows cannot be entirely explained by significant improvements in turbulent stress estimates in general, but is instead due to better prediction of the particular turbulent stress combinations which appear in the mean streamwise vorticity equation. As a consequence of this investigation, a new formulation of turbulent stress modification is proposed, which appears to better predict the turbulent stress distributions for a variety of flows: channel flow, equilibrium boundary layers, pipe flow, separated boundary layers and square duct flow.

The design and performance quantification of four Vertical Take-Off and Landing (VTOL) architectures for a canard-type aircraft configuration are presented. The aero-structural sizing of the canard configuration and the sizing procedure for the proposed VTOL configurations are described and discussed. The proposed VTOL architectures are based on a range of rotor distances to the centre of gravity, quad- and tri-rotor configurations, retractable front rotors and tilt rear rotors. The aerodynamic performance, total installed power and VTOL system mass were modelled and experimentally validated. The results show that a fully exposed VTOL system penalises the Lift-over-Drag (L/D) ratio significantly relative to a clean configuration. The VTOL system mass can be reduced by up to 32% by using a tilt tri-rotor configuration when compared with an equidistant quad-rotor+pusher configuration. The fraction of installed power usable for forward flight can be increased by up to 80% with a tilt configuration. For the proposed mission, the range can be significantly increased if a tri-rotor tilt configuration is adopted in place of an equidistant quad-rotor+pusher configuration.

An efficient, fully coupled beam model is developed to analyse laminated composite thin-walled structures with arbitrary cross-sections. The Euler–Lagrangian equations are derived from the kinematic relationships for a One-Dimensional (1D) beam representing Three-Dimensional (3D) deformations that take into account the cross-sectional stiffness of the composite structure. The formulation of the cross-sectional stiffness includes all the deformation effects and related elastic couplings. To circumvent the problem of shear locking, exact solutions to the approximating Partial Differential Equations (PDEs) are obtained symbolically instead of by numerical integration. The developed locking-free composite beam element results in an exact stiffness matrix and has super-convergent characteristics. The beam model is tested for different types of layup, and the results are validated by comparison with experimental results from literature.

The research focuses on the design space optimisation of National Advisory Committee for Aeronautics (NACA) submerged inlets through the formulation of a hybrid data fusion methodology. Submerged inlets have drawn considerable attention owing to their potential for good on-design performance, for example during cruise flight conditions. However, complexities due to the geometrical topology and interactions among various design variables remain a challenge. This research enhances the current design knowledge of submerged inlets through the utilisation of data mining and Computational Fluid Dynamics (CFD) methodologies, focusing on design space optimisation. A two-pronged approach is employed where the first step encompasses a low-fidelity model through data mining and surrogate modelling to predict and optimise the design parameters, while the second step uses the Design of Experiments (DOE) approach based on the CFD results for the candidate design geometry to construct a surrogate model with high fidelity for design refinement. The feasibility of the proposed methodology is demonstrated for the optimisation of the total pressure recovery of a NACA submerged inlet for the subsonic flight regime. The proposed methodology is found to provide good agreement between the surrogate and CFD-based model and reduce the optimisation processing time by half in comparison with conventional (global-based) CFD optimisation approaches.

We previously described an efficient, lightweight and flexible electro-thermal system, based on directly drawn carbon nanotube web (CNT web), as part of an icing protection system for carbon fibre reinforced polymer (CFRP) composite aircraft structures. The location of the heating elements on critical lifting surface leading edges or nacelle intake lips makes them particularly susceptible to impact damage, which may leave no visible mark. This makes it desirable to have both a mechanism for identifying the location of damage to the CNT structure (and by inference, potential damage to the underlying CFRP) and a process for restoring the CNT heater to full operation. With the CNT web acting as a sensor, impact damage is identified by an increase in electrical resistance and, particularly, by infrared imaging, which reveals a cold spot or zone depending upon the CNT web layup. Whereas a unidirectional CNT web layup exhibits a large increase in resistance and loss of a full width band of operation, a cross ply quasi-isotropic CNT web arrangement suffers only a small increase in resistance and a loss of function that is highly localised to the damaged area. A novel methodology, based on dispersed CNT in resin, is described for repairing and reconnecting the CNT structure and restoring functionality. A CNT web-based electro-thermal element was applied to the leading edge of a representative carbon-fibre composite wing section to demonstrate the flexibility of this system.

An electric propulsion model for propeller-driven aircraft is developed with the aim of minimising the power consumption for a given airspeed and thrust. Blade Element Momentum Theory (BEMT) is employed for propeller performance predictions fed with aerodynamic aerofoil data obtained from a proposed combined Computational Fluid Dynamics (CFD)–Montgomerie method, which is also validated. The Two-Dimensional (2D) aerofoil data are corrected to consider compressibility, three-dimensional, viscous and Reynolds-number effects. The BEMT model showed adequate fitting with experimental data from the University of Illinois Urbana Champaign (UIUC) database. Additionally, Goldstein optimisation via vortex theory is employed to design pitch and chord distributions minimising the induced losses of the propeller. Particle swarm optimisation is employed to find the optimal value for a wide range of geometrical and operational parameters considering some constraints. The optimisation algorithm is validated through a study case where an existing optimisation problem is approached, leading to very similar results. Some trends and insights are obtained from the study case and discussed regarding the design of an optimal propulsion system. Finally, CFD simulations of the study case are carried out, showing a slight relative error of BEMT.

The number of unmanned aerial vehicles (UAVs, also known as drones) has increased dramatically in the airspace worldwide for tasks such as surveillance, reconnaissance, shipping and delivery. However, a small number of them, acting maliciously, can raise many security risks. Recent Artificial Intelligence (AI) capabilities for object detection can be very useful for the identification and classification of drones flying in the airspace and, in particular, are a good solution against malicious drones. A number of counter-drone solutions are being developed, but the cost of drone detection ground systems can also be very high, depending on the number of sensors deployed and powerful fusion algorithms. We propose a low-cost counter-drone solution composed uniquely by a guard-drone that should be able to detect, locate and eliminate any malicious drone. In this paper, a state-of-the-art object detection algorithm is used to train the system to detect drones. Three existing object detection models are improved by transfer learning and tested for real-time drone detection. Training is done with a new dataset of drone images, constructed automatically from a very realistic flight simulator. While flying, the guard-drone captures random images of the area, while at the same time, a malicious drone is flying too. The drone images are auto-labelled using the location and attitude information available in the simulator for both drones. The world coordinates for the malicious drone position must then be projected into image pixel coordinates. The training and test results show a minimum accuracy improvement of 22% with respect to state-of-the-art object detection models, representing promising results that enable a step towards the construction of a fully autonomous counter-drone system.