This thesis presents a complete vision-based navigation system that can plan and follow an obstacle-avoiding path to a desired destination on the basis of an internal map updated with information gathered from its visual sensor. For vision-based self-localization, the system uses new floor-edges-specific filters for detecting floor edges and their pose, a new algorithm for determining the orientation of the robot, and a new procedure for selecting the initial positions in the self-localization procedure. Self-localization is based on matching visually detected features with those stored in a prior map. For planning, the system demonstrates for the first time a real-world application of the neural-resistive grid method to robot navigation. The neural-resistive grid is modified with a new connectivity scheme that allows the representation of the collision-free space of a robot with finite dimensions via divergent connections between the spatial memory layer and the neuro-resistive grid layer. A new control system is proposed. It uses a Smith Predictor architecture that has been modified for navigation applications and for intermittent delayed feedback typical of artificial vision. A receding horizon control strategy is implemented using Normalised Radial Basis Function nets as path encoders, to ensure continuous motion during the delay between measurements. The system is tested in a simplified environment where an obstacle placed anywhere is detected visually and is integrated in the path planning process. The results show the validity of the control concept and the crucial importance of a robust vision-based self-localization process.

The overall objective of this thesis was to develop field deployable instrumentation for the selective, sensitive determination of additives in diesel fuels using flow injection with chemiluminescence detection. The target analytes were the detergent dodecylamine and the lubricity additive P655. Chapter One describes the types of additives that are used in fully formulated diesel fuels in order to improve performance and outlines the need for robust analytical methods to be able to detect their presence / absences in fuels at the point of distribution, i.e. at the petrol pump. Flow injection (FI), and chemiluminescence (CL) are described as suitable techniques for sample preparation and detection respectively. The application of FI-CL for the quantitative determination of various analytes is reviewed, with the focus on real sample matrices. Finally the technique of solid phase extraction is discussed as a means of selective analyte preconcentration / matrix removal prior to FI-CL detection Chapter Two describes the development and optimisation (both univariate and simplex) of an FI-CL method for the determination of dodecylamine in acetonitrile / water mixtures using the catalytic effect of amines on the peroxyoxalate / sulphorhodamine 101 CL reaction. The linear range for dodecylamine was 0 - 50 mg Lˉ¹ with a detection limit of 190 µg Lˉ¹ and RSDs typically < 4 %. The effect of indigenous diesel compounds on the CL response is also investigated. Chapter Three investigates the applicability of the method developed in Chapter Two to determine dodecylamine in diesel fuels. Solid phase extraction was needed prior to analysis by FI-CL. The development of a solid phase extraction that is compatible with the FI-CL system is detailed. GC-NPD and GC-MS analysis are used in order to validate the solid phase extraction procedure. A range of diesel fuels have been spiked with an additive package containing dodecylamine and have been analysed off-line using FI-CL. Recoveries for all diesel fuels analysed were < 72 % and all fuels could by identified from the corresponding base fuel. Chapter Four describes the design and construction of a fully automated on-line solid phase extraction flow injection chemiluminescence analyser for the determination of dodecylamine in diesel fuel. Details of the automation and programming using LabVIEW are described. Results obtained using the automated on-line system are compared with results obtained using off-line SPE with FI-CL detection from Chapter Three. Recoveries for all fuels except SNV were < 71 %, and all fuels except SNV could be positively identified from the corresponding base fuels. No significant differences were found between the on-line and off-line results (within 95 % confidence limits). Chapter Five investigates the feasibility of determining the lubricity additive P655 in diesel fuel using FI-CL. The optimisation and development of a method using the competing reactions of periodate with alcohols and periodate with the CL oxidation reaction with pyrogallol is discussed, and the development of a solid phase extraction procedure for the extraction of P655 from an organic matrix is described. The limit of detection for P655 using SPE without preconcentration was 860 mg Lˉ¹ and was linear in the range 0 - 10000 mg Lˉ¹ (R² = 0.9965).

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Six sets of subscale carbon–carbon composite rotors and stators for aircraft brakes were manufactured to provide friction and wear test samples at six different densities. The friction and wear tests used energies to represent the service energy of the Boeing 767 aircraft. A functional relationship between fiction coefficient and porosity/density was made. This relationship was used to minimise manufacturing cost by providing the minimum densification of the carbon–carbon composite brake discs needed to meet design friction coefficient.

An aerodynamic shape optimisation capability based on a discrete adjoint solver for Navier-Stokes flows is developed and applied to a Blended Wing-Body future transport aircraft. The optimisation is gradient-based and employs either directly a Sequential Quadratic Programming optimiser or a variable-fidelity optimisation method that combines low- and high-fidelity models. The shape deformations are parameterised using a B´ezier-Bernstein formulation and the structured grid is automatically deformed to represent the design changes. The flow solver at the heart of this optimisation chain is a Reynolds averaged Navier- Stokes code for multiblock structured grids. It uses Osher’s approximate Riemann solver for accurate shock and boundary layer capturing, an implicit temporal discretisation and the algebraic turbulence model of Baldwin-Lomax. The discrete Navier-Stokes adjoint solver based on this CFD code shares the same implicit formulation but has to calculate accurately the flow Jacobian. This implies a linearisation of the Baldwin-Lomax model. The accuracy of the resulting adjoint solver is verified through comparison with finitedifference. The aerodynamic shape optimisation chain is applied to an aerofoil drag minimisation problem. This serves as a test case to try and reduce computing time by simplifying the fidelity of the model. The simplifications investigated include changing the convergence level of the adjoint solver, reducing the grid size and modifying the physical model of the adjoint solver independently or in the entire optimisation process. A feasible optimiser and the use of a penalty function are also tested. The variable-fidelity method proves to be the most efficient formulation so it is employed for the three-dimensional optimisations in addition to parallelisation of the flow and adjoint solvers with OpenMP. A three-dimensional Navier-Stokes optimisation of the ONERA M6 wing is presented. After describing the concept of Blended Wing-Body and the studies carried out on this aircraft, several aerodynamic optimisations are performed on this geometry with the capability developed in this thesis.

Helicopters are highly dependent on their transmission systems, which provide the vital links from the engines to the rotor and ancillary systems. Components are highly loaded and must be manufactured to a high degree of accuracy; the lack of redundancy implies that this is a 'series-chain' system. Existing techniques for calculating expected life are based upon historical data from different gearbox and helicopter types, thus limiting the confidence of the results. Design techniques may be conservative in some areas, whilst neglecting to consider different load patterns, usage, maintenance and environmental factors. This work describes the development of probabilistic models that represent damage accumulated by fatigue, wear and corrosion of the key components with an Intermediate gearbox (IGB). The parameters of these models represent geometrical, load and material data at the design stage, and produce an output in terms of failure probability against operating hours. This allows the influential parameters to be identified before building a prototype helicopter gearbox. The results from these models are then used to predict the upper and lower bounds of system reliability. This enables the combination of diverse failure mechanisms to be viewed to determine the relevant significance of each failure mechanisms. The effectiveness of the gearbox monitoring systems has been incorporated in the computer model by considering the probability of detection (POD) of each failure mechanism. The work to develop models found that there is a large body of work available to describe damage accumulation due to fatigue, but far less in regard to wear and corrosion. Fatigue models are very sensitive to load and material variability, particularly tooth root bending fatigue, for which many loads are considered 'non-damaging'. Wear models are mostly affected by changes in material hardness, wear coefficient and slip amplitude; changes in load are less influential on the predicted time to failure. The results for galvanic corrosion are dominated by the corrosion rate and time to initiate. In the system reliability model, reducing gear load appears to be the simplest means to increase life; increases in material strength and reduction in material variability are less achievable without significant improvements in manufacture and/or material technology.

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