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Electroplated cadmium coatings have been extensively used for many years in the military, marine and aerospace industries to provide corrosion protection to steel substrates. Cadmium coatings act as a barrier layer, protecting the substrate from corrosion attack. They continue to offer protection even when damaged. Cadmium deposits also offer sacrificial protection by preferentially corroding and galvanic protection to coated components in contact with other metals such as aluminium. However the hazardous nature of cadmium which is harmful to both humans and the environment, is a major issue. Started over 30 years ago, research into finding more environmentally-friendly alternatives continues as no substitute coating has yet been developed which could replace cadmium over the full range of applications. In this study, metallic AlCr(N) coatings containing 4 – 16 at% Cr and two different nitrogen contents (11-12 at% and 18 at%), were deposited by magnetron sputtering on stainless steel substrates - following initial coating deposition trials by both magnetron sputtering and electron-beam PVD. The coatings were then analysed to evaluate their mechanical, tribological and structural properties before being corrosion-tested using a novel AC/DC/AC cyclic test equipped with a pH monitoring system. The results indicate significant improvement in the mechanical (hardness range: 2 – 3.9 GPa) and tribological properties of the coatings with increasing alloying element content. In terms of corrosion performance, AlCr(N) with the lowest Cr content (i.e. 4 at%) displayed the best corrosion resistance properties owing to the formation of a thick and stable passive film within the pores as well as on the coating surface, providing excellent barrier corrosion protection. These promising results could be used to design graded Al-rich coatings in which individual layers are tailored to meet specific property requirements depending on the intended application, thereby enabling the replacement of cadmium on a range of steels and other engineering materials.

Positioning techniques have become an essential part of modern engineering, and the improvement in computing devices brings great potential for more advanced and complicated algorithms. This thesis first studies the existing radio signal based positioning techniques and then presents three developed methods in the sense of dealing with incomplete data. Firstly, on the basis of received signal strength (RSS) location fingerprinting techniques, the Kriging interpolation methods are applied to generate complete fingerprint databases of denser reference locations from sparse or incomplete data sets, as a solution of reducing the workload and cost of offline data collection. Secondly, with incomplete knowledge of shadowing correlation, a new approach of Bayesian inference on RSS based multiple target localisation is proposed taking advantage of the inverse Wishart conjugate prior. The MCMC method (Metropolis-within-Gibbs) and the maximum a posterior (MAP) / maximum likelihood (ML) method are then considered to produce target location estimates. Thirdly, a new information fusion approach is developed for the time difference of arrival (TDOF) and frequency difference of arrival (FDOA) based dual-satellite geolocation system, as a solution to the unknown time and frequency offsets. All proposed methods are studied and validated through simulations. Result analyses and future work directions are discussed.

This thesis introduces three new feature selection methods based on sequential orthogonal search strategy that addresses three different contexts of feature selection problem being considered. The first method is a supervised feature selection called the maximum relevance–minimum multicollinearity (MRmMC), which can overcome some shortcomings associated with existing methods that apply the same form of feature selection criterion, especially those that are based on mutual information. In the proposed method, relevant features are measured by correlation characteristics based on conditional variance while redundancy elimination is achieved according to multiple correlation assessment using an orthogonal projection scheme. The second method is an unsupervised feature selection based on Locality Preserving Projection (LPP), which is incorporated in a sequential orthogonal search (SOS) strategy. Locality preserving criterion has been proved a successful measure to evaluate feature importance in many feature selection methods but most of which ignore feature correlation and this means these methods ignore redundant features. This problem has motivated the introduction of the second method that evaluates feature importance jointly rather than individually. In the method, the first LPP component which contains the information of local largest structure (LLS) is utilized as a reference variable to guide the search for significant features. This method is referred to as sequential orthogonal search for local largest structure (SOS-LLS). The third method is also an unsupervised feature selection with essentially the same SOS strategy but it is specifically designed to be robust on noisy data. As limited work has been reported concerning feature selection in the presence of attribute noise, the third method is thus attempts to make an effort towards this scarcity by further exploring the second proposed method. The third method is designed to deal with attribute noise in the search for significant features, and kernel pre-images (KPI) based on kernel PCA are used in the third method to replace the role of the first LPP component as the reference variable used in the second method. This feature selection scheme is referred to as sequential orthogonal search for kernel pre-images (SOS-KPI) method. The performance of these three feature selection methods are demonstrated based on some comprehensive analysis on public real datasets of different characteristics and comparative studies with a number of state-of-the-art methods. Results show that each of the proposed methods has the capacity to select more efficient feature subsets than the other feature selection methods in the comparative studies.

Ti-6Al-4V drilled plates were subjected to cyclic loading tests in a previous study, which investigated the machining-induced effects on fatigue [1]. The majority of the specimens failed between low to moderate number of cycles, close to the surface of the hole, around the half thickness plane, with no clear crack initiation point. Differences in the performance of the plates were associated to the initiation of cracks from subsurface microstructure defects. However, a clear explanation of the mode of failure and the mechanisms behind it were not established due to the scattering of the fatigue data and the need for a more detailed examination of deformed microstructures and elastoplastic strain fields. This postulated the main research objective for the current study. A selected number of specimens after the fatigue tests were re-examined to identify the critical defects. The preliminary analysis included surface roughness, micro-hardness, LOM, and SEM of the machining-affected layer. Then, advanced characterization techniques, namely EBSD and FIB, were transformed into semi and fully quantitative methods to identify plastic strain gradients and residual stress profiles within the material. Despite the different drilling conditions, the specimens had similar roughness values. However, the plastic deformation and residual stress profiles within the material were directly related to each other and to the drilling conditions. All specimens displayed strain localization within smaller alpha grains of the sheared underlying microstructure, while tensile twins and slip bands were visible below the heavily deformed and strain hardened zone. Tensile, surface or near-surface stresses were measured for all drilling conditions at different locations around the hole. The results indicated that specimens with lower levels of deformation had superior fatigue performance. Since all specimens had identical defects, though to a different depth, it was deemed necessary to examine the fractured surface of the specimens. A closer inspection of the machined surfaces at the locations of the crack initiation revealed that chip fragments, embedded on the surface of the hole, were the critical defect dominating the fatigue life. Surface smearing and intense drilling marks were generating non-critical cracks. Chip cracking, voids within the chip, surface damage and cavities from the embedment of the chip, and shielding of surface twins by the chip were observed in the specimens. An exact description of the failure mechanism(s) was not possible because all of them appeared to be crack nucleation sites. The current study was concluded at this point providing the groundwork and the tools for future work.

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