This thesis describes an experimental investigation into the evolution of artificially generated high Reynolds number turbulent boundary layers (TBL). Due to its large importance on TBL scaling, skin friction has to be accurately determined. With this purpose, a robust post-processing method is developed to extract the mean skin friction and the wall-probe relative position from the mean velocity profile with uncertainties better than 1% and 0.5 wall units respectively. For disrupted TBLs, it is shown that, after a certain disturbance, TBLs evolve towards a canonical state after an adaptation region whose turbulent properties and length are strongly dependent on the trips' geometry. Two distinct mechanisms (so called wall-driven and wake-driven) are identified and associated with shorter and longer adaptation regions respectively. The latter is generated by disruptions exhibiting strong flow recirculation which enhances the influence of the obstacle's wake on the near-wall region and compromises the TBL properties in the adaptation region. Contrastingly, trips generating a wall-driven mechanism prevent this interaction from happening thus enabling a distinction between the trips' wakes and the near-wall region. Particle image velocimetry and low-order modelling of the flow in the close vicinity of the obstacles enable us to establish a three-way link between the main geometrical features of the trips, the length of the adaptation region and its turbulent properties. Low-porosity wall-mounted single- and multi-scale fences are designed and tested to control the degree of interaction between their wake and the near-wall region. Turbulent properties in the near-wall region are shown to scale with the local thickness of that internal layer rather than with the thickness of the whole fence's wake. Further, an aero-acoustic characterization of the flow is conducted showing the spatial distribution and the velocity scalability of the noise sources. Finally, some topics for further work are proposed.

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Improving the design of future high-Mach vehicles is crucial to enhance performance,safety and sustainability of future air travel. Advanced designs can be realized by improving low fidelity modelling in the context of Multidisciplinary Design Optimization (MDO) on one side and making the use of high fidelity tools more efficient in the context of Multi-fidelity Design Approaches (MFDA) on the other. This thesis presents the formulation of an advanced low order model for the estimation of the shock structure generated by vehicles flying in the supersonic and hypersonic regimes. Taking as inputs the geometry and the flow conditions, the proposed approach addresses, in one cohesive methodology, attached and detached shocks in two and three dimensions as well as shock structures composed of multiple shocks. The procedure is based on classical supersonic flow theories and has been verified against computational fluid dynamics simulations. The proposed methodology allows for a cost-effective estimation of shock wave patterns and their impingement on the vehicle surface on one side, while on the other it can be used to realize a-priori shock-fitted meshes reducing someof the uncertainty while generating them for high-fidelity CFD simulations.

A conceptual design optimization methodology was developed for a medium range box wing aircraft. A baseline conventional cantilever wing aircraft designed for the same mis- sion and payload was also optimized alongside a baseline box wing aircraft. An empirical formula for the mass estimation of the fore and aft wings of the box wing aircraft was derived by relating conventional cantilever wings to box wing aircraft wings. The results indicate that the fore and aft wings would use the same correction coe cient and that the aft wing would be lighter than the fore wing on the medium range box wing aircraft because of reduced sweep. As part of the methodology, a computational study was performed to analyze di erent wing/tip n xities using a statically loaded idealized box wing con guration. The analy- ses determined the best joint xity by comparing the stress distributions in nite element torsion box models in addition to aerodynamic requirements. The analyses indicates that the rigid joint is the most suitable. Studies were also performed to investigate the structural implications of changing only the tip n inclinations on the box wing aircraft. Tip n inclination refers to the angle the tip n makes to the vertical body axis of the aircraft. No signi cant variations in wing structural design drivers as a function of tip n inclination were observed. Stochastic and deterministic optimization routines were performed on the baseline box wing aircraft using the methodology developed where the variables were wing area, av- erage thickness to chord ratio and sweep angle. The conventional aircraft design showed similar performance and characteristics to the equivalent in-service aircraft thereby pro- viding some validation to the methodology and the results for the box wing aircraft. Longitudinal stability investigations showed that the extra fuel capacity of the box wing in the ns could be used to reduce trim drag. The short period oscillation of the conventional cantilever wing aircraft was found to be satisfactory but the box wing aircraft was found to be unacceptable hence requiring stability augmentation systems. The eld and ight performance of the box wing showed to be better than the conventional cantilever wing aircraft. Overall, the economic advantages of the box wing aircraft over the conventional cantilever wing aircraft improve with increase in fuel price making the box wing a worthy replacement for the conventional cantilever wing aircraft.

A take-off performance monitor is an instrument that is intended to monitor the progress of the take-off manoeuvre in real-time in order to ensure that the aircraft will meet the various distance constraints of the airfield. Several designs have to date been proposed but none have been successful commercially. This work has involved the development of a novel design concept based on the consideration of the time history of the run to obtain an accurate prediction of the distance required to VI. Scheduled post-VI distances are then allowed for in the estimate of the actual distances required to complete the manoeuvre. A performance standard complementing SAE aerospace standard AS-8044 has also been established to ensure system reliability during operation. The algorithms developed were validated using the College of Aeronautics' Jetstream-100 flying laboratory and take-off data of B747 and B737 aircraft. A fixed-base simulator was also used to evaluate the algorithm in adverse operating conditions. The algorithm was demonstrated to meet the named performance standards and is shown to have the potential of being utilised in a successful commercial performance monitor. A novel display design concept is also proposed, providing a basis on which an attractive display can be further developed.

In this research Pythagorean Hodograph based path planning and camera based cooperative perception are investigated separately and then these two entirely separate areas (Path Planning and Perception) are integrated for the application in online pop-up obstacle locating & avoidance and moving target tracking & surveillance in dynamic environments. The path planning is integrated with the cooperative perception to deal with the challenges posed by the dynamic environment. The aim of this integration is to achieve maximum autonomy required to execute a mission autonomously by multiple fixed wings UAVs in a dynamic environment. During the mission execution, the cooperating UAVs start from some initial location in the operating environment and finish at some final location while trying to achieve the mission’s objectives in a cooperative way. Naturally planning a feasible (safe and flyable) path for each participating UAV from initial position to a final location becomes a compulsory task of mission planning. For fixed wing UAVs flyable paths mean, paths which have tangential and curvature continuity and which obey the kinematic and dynamic constraint of the UAVs. In this research an algorithm based on Pythagorean hodograph curves is developed and used for planning feasible (safe and flyable) paths. The Pythagorean hodograph (PH) yields paths of exact length having tangential and curvature continuity. These continuous paths are made flyable for the UAVs by imposing the kinematic constraints of the UAVs. These constraints are imposed by the curvature and torsion manipulation of the planned paths. The safety of these paths is ensured by making it free of inter collisions between the vehicles and collisions with the known obstacles. These feasible paths are known as the initial paths or reference trajectories. In this research the operating environment is assumed to be dynamic in which changes are taking place at all times. Each UAV taking part in the mission is equipped with a vision sensor to perceive these changes continuously in a cooperative way. As the mission is assumed to be executed in day light, therefore light intensity video camera is used as a vision sensor. A perception algorithm for locating an object cooperatively in 3D is developed in this research. This algorithm is based on the optimization of errors in target position acquired by the on board camera. The algorithm is used by the cooperative perception system for optimal position estimation of the object in the scene. The target position information between the participating UAVs is exchanged through wireless communication for data fusion purposes. After developing efficient algorithms for path planning and cooperative perception, the two algorithms are integrated to be used in reactive obstacle avoidance and target tracking. During the mission, when the UAVs start their flight on the reference trajectories generated by the path planning algorithm, the perception algorithm comes into action. During the travel on these paths if the perception system of any of the UAVs detects an interrupting obstacle which was not known a priori in the map, then the exact location of this obstacle is determined with the help of the perception algorithm in a cooperative way. Using the location of the interrupting obstacle determined by the perception algorithm the path planning algorithm plans an evasive manoeuvre for the corresponding UAV to avoid it. After avoiding the obstacle the UAV comes back to its reference trajectory as soon as possible. In the operation of surveillance and tracking during the mission, the onboard perception algorithm locates an object of interest dynamically and the Pythagorean hodograph (PH) path planner uses this location to generate the paths for the cooperating UAVs to keep in close proximity of the target. In this case the close proximity of the target means to follow the moving target in such a way that it remains in the fields of views of the UAVs cameras at any time. By this integration of path planning and cooperative perception the continuous surveillance and tracking of the target was made possible even when the individual UAV experiences failure. During this research the mid flight obstacle locating & avoidance, and target surveillance & tracking have been successfully achieved by the integration of the path planning and cooperative perception. The purpose of this integration is to achieve an enhanced autonomy for the cooperating group of UAVs to increase the probability of their survival in mission being executed in dynamic environments.

This research investigates the use of small and low-cost UAVs (Unmanned Aerial Vehicles) for autonomous aerial surveillance, which aims to identify and continuously track suspicious vehicles and disguised threats in the ground traffic. Since typical ground traffic in an urban environment is quite dense and involves numerous vehicles, achieving this surveillance capability by a single mobile plat¬form is unlikely to be feasible in many aspects. In particular, due to physical constraints, it might be difficult for one UAV to cover large areas simultaneously, which is often critical to mission success in a rapidly changing environment. Be¬sides, in order to obtain accurate information of ground traffic, a single UAV platform will need to rely on sensors which are expensive yet vulnerable to the failure of the platform or sensing block by obstacles. Using multiple UAVs with relatively cheap aboard sensors with information fusion techniques enhancing sensing accuracy could resolve above issues of a single platform without signifi¬cantly increasing an operational cost. Therefore, this thesis deals with the surveillance application of multiple air¬borne sensor platforms endowed with an appropriate level of autonomous de¬cision making to support human operators. A group of UAVs become multiple mobile sensor platforms, and tasks/routes of each UAV need to be efficiently and optimally planned to cooperatively achieve mission objectives. Efficient and sophisticated algorithms for data acquisition/analysis, information fusion, path planning and formation reconfiguration ensuring feasible and safe cooperation, and decision making for cooperative missions are essentially to be developed, in order to take advantage of multiple aerial sensing sources for surveillance. Among various techniques for autonomous surveillance as listed above, this the¬sis seeks to develop and (partly) integrate some of important components: search route planning, behaviour identification/recognition, and moving target tracking, while examining benefits and drawbacks of using multiple UAVs. A particular focus is on multi-sensor management and information fusion in consideration of physical constraints of the platform and strict real-time requirements of the applications in uncertain and dynamic environments. This research investigates the use of small and low-cost UAVs (Unmanned Aerial Vehicles) for autonomous aerial surveillance, which aims to identify and continuously track suspicious vehicles and disguised threats in the ground traffic. Since typical ground traffic in an urban environment is quite dense and involves numerous vehicles, achieving this surveillance capability by a single mobile plat-form is unlikely to be feasible in many aspects. In particular, due to physical constraints, it might be difficult for one UAV to cover large areas simultaneously, which is often critical to mission success in a rapidly changing environment. Be-sides, in order to obtain accurate information of ground traffic, a single UAV platform will need to rely on sensors which are expensive yet vulnerable to the failure of the platform or sensing block by obstacles. Using multiple UAVs with relatively cheap aboard sensors with information fusion techniques enhancing sensing accuracy could resolve above issues of a single platform without signifi-cantly increasing an operational cost. Therefore, this thesis deals with the surveillance application of multiple air-borne sensor platforms endowed with an appropriate level of autonomous de-cision making to support human operators. A group of UAVs become multiple mobile sensor platforms, and tasks/routes of each UAV need to be efficiently and optimally planned to cooperatively achieve mission objectives. Efficient and sophisticated algorithms for data acquisition/analysis, information fusion, path planning and formation reconfiguration ensuring feasible and safe cooperation, and decision making for cooperative missions are essentially to be developed, in order to take advantage of multiple aerial sensing sources for surveillance. Among various techniques for autonomous surveillance as listed above, this the¬sis seeks to develop and (partly) integrate some of important components: search route planning, behaviour identification/recognition, and moving target tracking, while examining benefits and drawbacks of using multiple UAVs. A particular focus is on multi-sensor management and information fusion in consideration of physical constraints of the platform and strict real-time requirements of the applications in uncertain and dynamic environments. This thesis firstly proposes a road-network search planning algorithm by which UAVs are able to efficiently patrol every road identified in the map. A mixed integer linear programming problem (MILP) is formulated to find an optimal so¬lution minimising a total flight time, while accommodating physical constraints of the UAV with the Dubins path. To overcome the computational burden of the MILP, an approximation approach is also proposed. By running Monte Carlo sim¬ulation with the randomly generated maps, an efficient UAV team size and path planning method is examined. Secondly, this thesis proposes a behaviour recog¬nition methodology for ground vehicles moving within road traffic to identify abnormal behaviour. Ground vehicle behaviour is first classified into represen¬tative driving modes, and string pattern matching theory is applied to detect suspicious behaviours in the driving mode history. Moreover, a fuzzy decision making process is developed to systematically exploit all available information obtained from a complex environment considering spatiotemporal environment factors as well as several aspects of behaviours. Lastly, to achieve continuous tracking of detected suspicious vehicles for closer and higher-resolution surveil¬lance data, this thesis proposes several coordinated standoff tracking guidance algorithms using multiple UAVs. The effect of the improved target estimation accuracy on the tracking guidance performance is also examined using roadmap information and sensor fusion techniques. From this thesis, it can be identified that following aspects need to be carefully considered to realise autonomous surveillance using multiple UAVs: i) how many UAVs/sensors would be enough to perform a mission in terms of efficiency, es¬timation accuracy and guidance performance, ii) information gathered by UAVs only is enough, or domain knowledge (local context and past experience) might be additionally required, iii) communication structure between UAVs, and iv) com¬putation time. The proposed autonomous surveillance system utilising multiple UAVs is expected to greatly increase the amount of area that can be continuously monitored, while reducing the number of human operators and their workload required to analyse surveillance data and respond to identified targets.

An experimental study has been performed to evaluate the effect of a cold axial jet on a variety of typical aircraft wake vortex systems in the near-field. This research attempted to alleviate the vortex hazard imposed on trailing aircraft, which is especially important in the crowded skies around airfields.

In this research we look at the effects of heating a single vertical wall bounding a semi-infinite fluid. This investigation is based on a mathematical and numerical study of the equations that govern the fluid motion. Our main focus is on the study of thermal instabilities, the first stage in the breakdown of the smooth flow up the wall that may eventually lead to turbulence. In our research, a thermal instability is defined to be a growth in the disturbance energy by a set amount. Initially instabilities cannot develop and therefore the main aim of our research is to identify the time at which instabilities in our system begin to grow. This involves finding the most unstable initial conditions and looking at how the form of the instabilities change as the background flow evolves. By achieving this, we have obtained quantitative information regarding the onset of thermal instabilities which takes into account the time-dependent nature of the problem.

This work describes the research undertaken on the development of adaptive structures to reduce turbulent boundary layer separation from a wing. Separation control is a safety critical function that is currently filled by the application of static vortex generators to the wings on most modern aircraft. These devices generate vorticity which produces a downstream mixing effect, energising the boundary layer and postponing separation. The mixing of the boundary layer also increases the drag of the aircraft, reducing efficiency. As static devices, the mixing effect is also permanent, regardless of the current likelihood of separation. Adaptive structures allow the development of beneficial geometry from the body's surface without the use of breaks or mechanisms in the structure surface. This allows geometry modification without sources of parasitic drag or turbulent transition. The first subject of this work is the development of an adaptive surface to provide the desired momentum transfer through the boundary layer when required, and which can be retracted when not needed, reducing drag and increasing efficiency. Adaptive structures inhabit a complex design space due to the coupling between bending and in-plane stretching of the surface. In previous morphing studies, design optimisation has frequently been used to identify the ideal design parameters. Initially, the design methodology is developed on a test case transferring momentum within a zero-pressure gradient boundary layer. The resulting geometry is then tested experimentally and the structural and fluidic response is found to compare well to simulations. Once the design approach is validated, it must be applied to an efficient location on an aerofoil. The second area of research is therefore the complex, three-dimensional, separation from a 2D aerofoil. This is investigated experimentally with both mean and time-dependent data. The naturally occurring, three-dimensional and spanwise periodic topology of the separated flow, termed a 'stall cell', is investigated to determine a suitable location for the application of targeted control at a critical point. Fourier analysis and Proper Orthogonal Decomposition are applied to the time-dependent data gathered to extract coherent, periodic, fluctuations in the separated flow field. The variation of the relative strengths of these features, distinct in frequency, is isolated to regions within the stall cell. Knowledge of the flow field gained during this work is applied to stall cell reduction and a single vortex generator is applied to the wing upstream of an identified critical point within the flow field. The separated area is seen to reduce significantly with this actuation. The design methodology developed previously is applied to the initially curved surface of an aerofoil. The final structure is manufactured and tested experimentally and found to be effective in reducing the separation extent. The control is found to be less effective than the static vortex generators. However, unlike the static device, the adaptive version is fully elastic, in both deployment and reaction, and thus shows none of the detrimental effects associated with traditional devices.