By using the method of elastic neutron scattering, structure factors were measured for the chalcogens tellurium, selenium and sulphur in the liquid state. Partial structure factors were also obtained for the liquid semiconductors Cu2Te, CuTe and Ag2Te. By Fourier transforming these structure factors radial distribution functions (R.D.F's) were found. Structural models consisting of ionic bonding, covalent bonding and clusters were compared with the experimental data, and the interpretation was aided by the construction of computer models by a ' Monte-Carlo' method. It was concluded that the liquid semiconductors investigated have a complex structure with mainly covalent bonding; also that liquid selenium consists of chains of atoms and liquid tellurium has a network structure similar to that outlined by Cabane and Friedel (1971).

The influence of the upstream presence of small two-dimensional surface discontinuities on the downstream characteristics of the separated turbulent boundary-layer flow in which they are immersed was studied both experimentally and by means of an appropriate boundary layer prediction model. In the experimental part, flow separation induced by an adverse pressure gradient was established first over a smooth surface. Different sizes of surface discontinuities of mainly square cross-section have been spanned across the surface upstream at different positions. Measurements were made at various stations of mean velocity profiles, wall skin friction, and longitudinal normal stress component distributions both with and without the surface discontinuities being present. Boundary layer integral parameters and drag coefficients were deduced from the measured velocity profiles. The pulsed-wire anemometer was used for the bulk of these measurements. Pitot and Preston tubes were also used in regions where the flow was less unsteady. The lag-entrainment integral prediction method was employed to determine two-dimensional separated flow characteristics. The method is used in an inverse mode in which the displacement thickness is specified and the pressure distribution is predicted together with other boundary layer integral parameters. The presence of the surface discontinuities was modelled and methods for continuing the boundary layer prediction process across and then downstream of these discontinuities were developed. Satisfactory agreement with the experimental data was obtained which suggests that the developed technique provides an adequate computation procedure for this application. Taking into account both the experimental results and the computer predictions, the investigation reveals that the presence of small surface discontinuities upstream does not greatly affect the separation process downstream, either in its location or its flow characteristics. However, when this surface discontinuity height is larger than the height of the boundary layer logarithmic region the downstream separation point is moved to the location of the surface discontinuity.

This research describes the development of a computer based design advice system intended specifically to aid small companies in the application of rapid prototyping. To accomplish this firstly required a thorough review of the current state of the art in prototyping technologies and associated processes. Through interviews with industry professionals this review included an assessment of the actual operational capabilities found in industry as opposed to theoretical performance measures. From this data, rules were created to quantify and rank the performance of the different technologies according to parameters that are the most readily available and easily understood by the user. It was also necessary to devise a method of specifying the users' requirements of the prototype. Providing as much automation as possible, required the development of software capable of reading in CAD data and deriving from it the parameters that would most affect the suitability of a rapid prototyping process. Further software was developed to calculate realistic and reliable estimations for the costs and lead times associated with different possible routes. Explanatory material was added to the system to describe and illustrate how the different technologies worked, such that with continued use, the user could become familiar with rapid prototyping. Unlike previous attempts at producing a rapid prototyping selection system, the one described here was tested with target users and verified against the opinion of an industry expert. The resulting system was found to be quick and simple to operate providing all of the required information whilst incurring the minimum of hindrance to the users' normal tasks.

This thesis presents the results of new techniques investigated for applying on-line sketching into 2D and 3D conceptual design geometry throughout a whole development process: data collection, concrete curve segmentation and fitting, 2D geometric constraint extraction and solver, and 3D feature recognition and modelling. This is a new approach. A real time sketch and fuzzy knowledge-based prototype system has been developed in four phases. In the first phase, the segmentation approach investigated accepts the input of on-line free-hand sketch, and segments them into meaningful parts, by using fuzzy knowledge in terms of sketching position, direction, speed and acceleration. During the second phase, a parallel curve classification and identification method is studied by employing fuzzy heuristic knowledge in terms of curve linearity and convexity, in order to quickly classify and identify a variety of 2D shapes including straight lines, circles, arcs, ellipse, elliptical arcs, and free-form curves. Afterwards, a geometric constraint inference engine and a constraint solver are utilised according to degrees of freedom analysis, to capture a designer's intention, to infer geometric constraints simply and automatically, and to generate a possible solution without involving iterative computing. The solver also supports variational geometry in 2D and 3D. In the last phase, rule-based feature interpretation and manipulation techniques are investigated. While drawing, the 2D geometry is accumulated until it can be interpreted as a 3D feature. The feature is then placed in the 3D space and a new feature can be built incrementally upon previous versions. The given examples and case studies show that the system can interpret users' intention on 2D and 3D geometry satisfactorily and effectively. It can not only accept sketched input, but also users' menu-based interactive input of 2D primitives and 3D projections' This mixed automatic feature interpretation and interactive design environment can encourage designers with poor sketching skills to use it for creative design tasks.

The alarming growth of antibiotic-resistant superbugs including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE) is driving the development of new technologies to investigate antibiotics and their modes of action. Novel cantilever array sensors offer a tool to probe the nanomechanics of biomolecular reactions and have recently attracted much attention as a ’label-free’ biosensor as they require no fluorescent or radioactive tags and so biomolecules can be rapidly assayed in a single step reaction. Thereby, cantilever-based sensors are unique in the sense that they can measure an in-plane nanomechanical surface stress which is not purely mass dependent. This thesis reports the label-free detection of drug-target interactions on microfabricated cantilever arrays focusing on the vancomycin family of antibiotics. Vancomycin has remained at the forefront of the battle against MRSA and works by targeting the outer cell wall of bacteria, nevertheless little is known about how the drug binding interactions lead to a large scale mechanical weakening of the cell and consequently cell death by lysis. In this thesis three key developments are reported: (i) the development of experimental protocols and cantilever instrumentation to enable robust, specific and sensitive drug-target measurements in buffer and blood serum, (ii) a detailed investigation of the nanomechanical transduction mechanism which identified a critical density of surface ligands for the generation of stress and may have important implications on the mechanical mode of action of glycopeptides on the bacteria cell wall, and (iii) the first use of this technology to analyse drug targets on tethered lipid layers that closely mimic the surface of bacteria. These findings and underlying concepts represent major milestones for this promising technology and may also contribute to our understanding of how antibiotics actually kill bacteria and thereby advance the search for a new generation of drugs in the battle against superbug resistance.

Automatic face recognition has been an active research area for the last four decades. This thesis explores innovative bio-inspired concepts aimed at improved face recognition using surface normals. New directions in salient data representation are explored using data captured via a photometric stereo method from the University of the West of England’s “Photoface” device. Accuracy assessments demonstrate the advantage of the capture format and the synergy offered by near infrared light sources in achieving more accurate results than under conventional visible light. Two 3D face databases have been created as part of the thesis – the publicly available Photoface database which contains 3187 images of 453 subjects and the 3DE-VISIR dataset which contains 363 images of 115 people with different expressions captured simultaneously under near infrared and visible light. The Photoface database is believed to be the ?rst to capture naturalistic 3D face models. Subsets of these databases are then used to show the results of experiments inspired by the human visual system. Experimental results show that optimal recognition rates are achieved using surprisingly low resolution of only 10x10 pixels on surface normal data, which corresponds to the spatial frequency range of optimal human performance. Motivated by the observed increase in recognition speed and accuracy that occurs in humans when faces are caricatured, novel interpretations of caricaturing using outlying data and pixel locations with high variance show that performance remains disproportionately high when up to 90% of the data has been discarded. These direct methods of dimensionality reduction have useful implications for the storage and processing requirements for commercial face recognition systems. The novel variance approach is extended to recognise positive expressions with 90% accuracy which has useful implications for human-computer interaction as well as ensuring that a subject has the correct expression prior to recognition. Furthermore, the subject recognition rate is improved by removing those pixels which encode expression. Finally, preliminary work into feature detection on surface normals by extending Haar-like features is presented which is also shown to be useful for correcting the pose of the head as part of a fully operational device. The system operates with an accuracy of 98.65% at a false acceptance rate of only 0.01 on front facing heads with neutral expressions. The work has shown how new avenues of enquiry inspired by our observation of the human visual system can offer useful advantages towards achieving more robust autonomous computer-based facial recognition.

According to G59 recommendation, the common practice adopted by utilities in the UK is to disconnect Distributed generators (DGs) immediately once a network fault is detected to prevent islanding operation and disruption of the operation of conventional auto-reclosing schemes. However, with the continuous increase of penetration of DGs into existing distribution networks, it is becoming increasingly important that DGs must support power networks during steady-state and fault conditions. It has been recognised that 80% of faults in distribution networks are temporary and most of them are single-line-to-ground (SLG) faults. This should give a strong incentive to find ways for maintaining DGs in service during temporary SLG faults as far as possible which would benefit utilities, DG developers and customers. The literature survey shows that no research work has been carried out to investigate a fault identification and phase selection algorithm suitable to be used in a novel single-phase auto-reclosing (SPAR) scheme, specifically suitable to distribution networks with DGs, for maintaining the continued operation of DGs during fault conditions. The work in this PhD has focused on investigating feeder protection requirements for continued operation of DGs in radial and ring overhead distribution networks with DGs, particularly the new requirements for operating an auto-reclosing scheme in networks with DGs. Simulation results obtained from this investigation have revealed that it is a possible to maintain continued operation of DGs that are based on DFIG and FSIG during temporary SLG faults in radial and ring operated networks. This is followed by investigating the development of an adaptive fault identification and phase selection algorithm suitable for a SPAR scheme in a power system with DGs. The proposed fault identification and phase selection algorithm uses only the three line currents measured at the relay point. The waveform pattern of phase angle and symmetrical components of the three line currents during the transient period following a fault condition is analysed using IF-THEN condition-based rules in order to determine the type of SLG fault. The verification test results have revealed that the proposed method can correctly detect the faulty phase within one cycle in a distribution network with DGs under various network operating and fault conditions. The work in this PhD has resulted in publication of papers (see Appendix I).

Production of hydrocarbon from both consolidated and unconsolidated clastic reservoir rocks poses a risk of sand production especially if a well articulated programme of sand management strategy is not put in place to deal with the problem at the onset of field development. A well articulated programme of sand management would include sand production potential prediction in real time if it is going to be effective at all in achieving the goal of dealing with likely sand problem. Sanding potential prediction in real time is considered an element of sand management strategy that involves the evaluation of risk of sand failure/production and the prediction of the likely sand rate and volume to facilitate optimum design of both downhole and surface equipment especially as related to sand control. Sanding potential prediction is therefore very crucial to reducing costs of field developments to make hitherto unattractive development environments profitable. This undoubtedly will impact positively the present drive to increase worldwide production of hydrocarbon . Specifically, real time sanding potential prediction enables timely reservoir management decisions relating to the choice, design and installation of sand control methods. It is also an important input to sand monitoring and topside management. The current sanding potential prediction models in the industry are found to lack the robustness to predict sanding potential in real time. They also are unable to provide the functionality to track the grain size distributions of the sand producing formation and that of the produced sand. This functionality can be useful in the application of grain size distribution to sanding potential prediction. The scope of this work therefore covers the development of coupled models for grain size distribution and sanding potential predictions in real time. A previous work has introduced the use of a commercial neural network technique for grain size distribution prediction. This work has built upon this by using a purposefully coded neural network in conjunction with statistical techniques to develop a model for grain size distribution prediction in both horizontal and vertical directions and extending the application to failure analysis and prediction of strength and sanding potential in formation rocks. The theoretical basis for this work consists in the cross relationships between formation petrophysical properties and grain size distribution parameters on one hand and between grain size distribution parameters and formation strength parameters on the other hand. Hoek and Brown failure criterion, through an analytical treatment, serves as the platform for the development of the failure model, which is coupled to the grain size distribution and Unconfined Compressive Strength (UCS) models. The results obtained in this work have further demonstrated the application of neural network to grain size distribution prediction. They also demonstrate that grain size distribution information can be used in monitoring changes in formation strength and by extension, the formation movement within the failure envelope space especially during production from a reservoir formation.

The increases in Greenhouse Gas (GHG) concentrations and depletion of hydrocarbon based fuels have become global concerns. As a result, a number of methods are being developed which aim to restrict GHG and to develop alternative fuels from sustainable sources. Photocatalysis has shown potential to restrict GHG through CO2 recycling and convert solar energy to alternative fuels through solar H2 production. This thesis describes the development of photo reactors to reduce CO2 emissions and to provide a novel method of producing H2 as a fuel source. A number of photo reactors were developed including three fluidised design concepts and a thin film system. The preliminary evaluation of the reactors was performed using methyl orange (MO) as a model compound and utilising TiO2 and ZnO. The reduction of CO2 and H2 evolution was performed over a range of novel catalysts in the optimised system developed, referred to as the propeller fluidised photo reactor (PFPR). A MO photodegradation efficiency of > 95 % was achieved in all the photo reactors using illumination from a low power 36 W lamp. The reduction of CO2 was performed in the PFPR under varying illumination sources including UV, simulated and natural solar exposure. CO2 reduction was not achieved in the unit under any experimental conditions. However, the evolution of H2 was achieved under both simulated and natural solar irradiation. The results demonstrated that reactor properties such as propeller rotational speed were found to enhance the photo activity of the system through the elimination of mass transport limitations and increasing light penetration. The optimum conditions for H2 evolution were found to be a propeller rotational speed of 1035 rpm and 144 W of simulated solar irradiation, which produced a rate of 109 μmol h-1 g-1 over Pt-C3N4. Under solar irradiation 8 μmol h-1 g-1 was evolved over NaTaO3.La. The rate of H2 evolution over Pt-C3N4 increased from 27 to 109 μmol h-1 g-1, upon increasing the rotational speed of the propeller from 0 to 1035 rpm. Furthermore, the use of the PFPR with solar irradiation displayed the potential for solar photocatalysis applications.

There are anticipated to be substantial global deposits of land and seabed methane gas hydrates. The volume of methane gas trapped in these methane gas hydrates is calculated to be at least twice the volume of current global reserves of oil & gas as reviewed by the United Nations. These methane gas hydrates are deemed important as a future energy resource, and several companies and countries are looking at the effective exploitation of the resource for methane gas supply. If safe economic exploitation could be achieved the world will have an energy resource that would be able to support the demands for century's to come. The chemistry, physics and geological setting of the natural hydrates make them difficult to exploit using convention hydrocarbon well engineering techniques. The major nations of the world such as the United States of America, Japan, Canada, France and Germany are investing heavily in research and development to gain a better understanding of the gas hydrate energy source. It is an area that we will see confirmed as a major energy source for the world, provided the costs of development can be reduced. In the perma frost land environment and deep sea marine environment Hydrates have traditionally been seen as a major risk to Drilling operations and have been implicated with many drill well blowouts world wide. This thesis critically reviews the existing industry approaches to hydrate exploitation and proposes several new well engineering techniques, which could be applied to effect successful resource recovery. This thesis derives the conclusion that by an enhanced understanding of the deposit area and by the application of new well technology and varied procedures, methane exploitation will be possible. The thesis focused on three areas to reduce cost of development: 1. Low cost, low complexity, subsea systems to drill produce and maintain developments. 2. Utilisation of fit for purpose low cost vessels to conduct the field development drilling and completion. 3. Seabed drilling topdrive system to enable rapid drilling of the development.