‘Climate change’ and ‘defence’ are becoming closely associated topics, particularly in relation to the potential that the defence sector has to support the development of low carbon technologies. This exploratory research applies an inductive approach and a strongly archival strategy in order to investigate how Organisational Carbon Accounting (OCA) practices in the defence sector can best support low carbon technology innovation. It takes an interdisciplinary approach to the literature, drawing on the fields of Carbon Accounting, Defence Industrial Policy, and Innovation Studies. It finds that there some difficulties allocating emissions to organisations in existing OCAs, which are particularly marked in the defence sector due to close working relationships between organisations. These allocations can result in abstract OCAs that do not always reflect the underlying activities causing emissions to be produced. In contrast, ‘Project Level’ Carbon Accounts focused on large-scale collaborative programmes can better account for the emissions of the defence sector in an understandable way that engages new and relevant actors to defence-energy debates. These accounts are therefore more likely than existing OCA practices to support low carbon technology development across innovation networks. A positive selection environment for low carbon technologies can be promoted if these ‘Project-Level’ Carbon Accounts are presented within an appropriate strategic framework, and this research describes the relevance of the defence sector concepts of ‘resilience’ and ‘endurance’ and the related metric of the Fully Burdened Cost of Energy (FBCE). The findings emphasise the value of sector-level analyses of OCA practices, which are not represented in the literature at present. The sector-level perspective can help identify relevant methods from the wider Carbon Accounting field that can improve existing organisational approaches. More importantly, it can help researchers engage with the fundamental question of what Carbon Accounting is for, by analysing how the OCA practices within a specific sector support or inhibit its most effective contribution to climate change mitigation.

Housing sectors have particular significance and impact on resource use, deployment and sustainability. Given this, they are inextricably enmeshed in a raft of conjoined issues, ranging from energy, production and consumption, through to effective governance structures and leveraged sustainable transformations. However, the real challenges facing the Housing sectors rest with the supportive societal structures which underpin the operationalisation of these issues. This includes such factors as consultation and engagement, and the identification of critical drivers and proven solutions – which are tangible barriers for sustainable transformations (particularly in the English housing system). This research presents a conceptual model – STRIDES (Strategic Tri-level Relational Interventions for Delivering Energy efficiency and Sustainability), which purposefully addresses the aforementioned barriers, and critically challenges thinking and engagement. STRIDES explicitly captures 5-INs, which embodies interrelated essential conditions needed for successful transformation. This conceptual model was developed using a mixed-method approach, engaging constructivism/interpretivism to guide the development and augmentation of this (to ensure maximum relevance and impact). The English housing system was used as the primary lens – which helped both shape and inform the research methodological approach. STRIDES was developed through: an online survey questionnaire (for systems-knowledge); Delphi questionnaires (for target-knowledge); and focus group discussions (for transformative-knowledge). The theoretical constructs and methods revealed exclusive hidden dialogue of composite correlated multi-perspective stakeholders, which highlighted tri-level influences on interdependent system-components for effective governance of sustainable transformations. Recognising and prioritising relationally responsive emerging strategies arising from STRIDES help stakeholders appreciate subtle nuances and forces across and beyond contexts. This helps positioning, especially to shape/tailor strategic interventions to deliver meaningful objectives of these sustainable transformations.

The main aims of the research are to develop various high-speed hardware circuits based on the latest electronic devices and integrated circuit technologies to provide time measurement with one picosecond accuracy, thereby enabling the development of a satellite laser ranging (SLR) system with submillimeter precision. Different types of oscillators and frequency multipliers have been developed (RF and microwave) in order to provide a synchronous and low phase noise clock signal to the SLR timing system, which is phase-locked to the Universal Time Clock (UTC). A technique to quantify phase noise in signal sources is presented and verified. The development of the ranging system encompasses the analog timing verniers, the digital timing system, acquisition and processing of the ranging data, and the controlling of the peripherals, like the laser. The mixed analog/digital timing system architecture provides a time interval determination of two events with picosecond accuracy. Optical calibration techniques and an electronic timing calibration technique were developed to provide calibration of the timing system down to one picosecond accuracy and femtoseconds of resolution, traceable to the International Standard (speed of light, metric standard). The work done has led to several electronic modules for measuring precisely laser runtimes to artificial satellites and to the Moon which are now in successful and permanent operation in five SLR stations around Tokyo, one SLR station in Australia, and one SLR station in Germany. Furthermore, the work has produced three papers and two patents and won the First Prize of Innovation Awards from Deggendorf Government. The research and development work pushed the picosecond timing technology to an extent where the SLR stations in Australia, Tokyo and Germany now have a significant improvement in their ranging data accuracy in comparison to their previous timing equipment, thereby achieving more precise environmental monitoring.

No description available.

This thesis introduces and develops a novel real-time predictive maintenance system to estimate the machine system parameters using the motion current signature. A crucial concept underpinning this project is that the motion current signature contains infor­mation relating to the machine system parameters and that this information can be extracted using nonlinear mapping techniques, such as neural networks. Towards this end, a proof of con­cept procedure is performed, which substantiates this concept. A simulation model, TuneLearn, is developed to simulate the large amount of training data required by the neural network ap­proach. Statistical validation and verification of the model is performed to ascertain confidence in the simulated motion current signature. Validation experiment concludes that, although, the simulation model generates a good macro-dynamical mapping of the motion current signature, it fails to accurately map the micro-dynamical structure due to the lack of knowledge regarding performance of higher order and nonlinear factors, such as backlash and compliance. Failure of the simulation model to determine the micro-dynamical structure suggests the pres­ence of nonlinearity in the motion current signature. This motivated us to perform surrogate data testing for nonlinearity in the motion current signature. Results confirm the presence of nonlinearity in the motion current signature, thereby, motivating the use of nonlinear tech­niques for further analysis. Outcomes of the experiment show that nonlinear noise reduction combined with the linear reverse algorithm offers precise machine system parameter estimation using the motion current signature for the implementation of the real-time predictive maintenance system. Finally, a linear reverse algorithm, BJEST, is developed and applied to the motion current signature to estimate the machine system parameters.

The thesis presents new methodology and algorithms that can be used to analyse and measure the hand tremor and fatigue of surgeons while performing surgery. This will assist them in deriving useful information about their fatigue levels, and make them aware of the changes in their tool point accuracies. This thesis proposes that muscular changes of surgeons, which occur through a day of operating, can be monitored using Electromyography (EMG) signals. The multi-channel EMG signals are measured at different muscles in the upper arm of surgeons. The dependence of EMG signals has been examined to test the hypothesis that EMG signals are coupled with and dependent on each other. The results demonstrated that EMG signals collected from different channels while mimicking an operating posture are independent. Consequently, single channel fatigue analysis has been performed. In measuring hand tremor, a new method for determining the maximum tremor amplitude using Principal Component Analysis (PCA) and a new technique to detrend acceleration signals using Empirical Mode Decomposition algorithm were introduced. This tremor determination method is more representative for surgeons and it is suggested as an alternative fatigue measure. This was combined with the complexity analysis method, and applied to surgically captured data to determine if operating has an effect on a surgeon’s fatigue and tremor levels. It was found that surgical tremor and fatigue are developed throughout a day of operating and that this could be determined based solely on their initial values. Finally, several Nonlinear AutoRegressive with eXogenous inputs (NARX) neural networks were evaluated. The results suggest that it is possible to monitor surgeon tremor variations during surgery from their EMG fatigue measurements.

The number of remote sensing platforms and sensors rises almost every year, yet much work on the interpretation of land cover is still carried out using either single images or images from the same source taken at different dates. Two questions could be asked of this proliferation of images: can the information contained in different scenes be used to improve the classification accuracy and, what is the best way to combine the different imagery? Two of these multiple image sources are MODIS on the Terra platform and ETM+ on board Landsat7, which are suitably complementary. Daily MODIS images with 36 spectral bands in 250-1000 m spatial resolution and seven spectral bands of ETM+ with 30m and 16 days spatial and temporal resolution respectively are available. In the UK, cloud cover may mean that only a few ETM+ scenes may be available for any particular year and these may not be at the time of year of most interest. The MODIS data may provide information on land cover over the growing season, such as harvest dates, that is not present in the ETM+ data. Therefore, the primary objective of this work is to develop a methodology for the integration of medium spatial resolution Landsat ETM+ image, with multi-temporal, multi-spectral, low-resolution MODIS \Terra images, with the aim of improving the classification of agricultural land. Additionally other data may also be incorporated such as field boundaries from existing maps. When classifying agricultural land cover of the type seen in the UK, where crops are largely sown in homogenous fields with clear and often mapped boundaries, the classification is greatly improved using the mapped polygons and utilising the classification of the polygon as a whole as an apriori probability in classifying each individual pixel using a Bayesian approach. When dealing with multiple images from different platforms and dates it is highly unlikely that the pixels will be exactly co-registered and these pixels will contain a mixture of different real world land covers. Similarly the different atmospheric conditions prevailing during the different days will mean that the same emission from the ground will give rise to different sensor reception. Therefore, a method is presented with a model of the instantaneous field of view and atmospheric effects to enable different remote sensed data sources to be integrated.

High velocity oxyfuel (HVOF) thermal spraying is one of the most significant developments in the thermal spray industry since the development of the original plasma spray technique. The first investigation deals with the combustion and discrete particle models within the general purpose commercial CFD code FLUENT to solve the combustion of kerosene and couple the motion of fuel droplets with the gas flow dynamics in a Lagrangian fashion. The effects of liquid fuel droplets on the thermodynamics of the combusting gas flow are examined thoroughly showing that combustion process of kerosene is independent on the initial fuel droplet sizes. The second analysis copes with the full water cooling numerical model, which can assist on thermal performance optimisation or to determine the best method for heat removal without the cost of building physical prototypes. The numerical results indicate that the water flow rate and direction has noticeable influence on the cooling efficiency but no noticeable effect on the gas flow dynamics within the thermal spraying gun. The third investigation deals with the development and implementation of discrete phase particle models. The results indicate that most powder particles are not melted upon hitting the substrate to be coated. The oxidation model confirms that HVOF guns can produce metallic coating with low oxidation within the typical standing-off distance about 30cm.

The possible evaporation of lubricant in fluid film bearings has been investigated theoretically and by experiment using a radial flow hydrostatic bearing supplied with liquid refrigerant R114. Good correlation between measured and theoretical values was obtained using a bespoke computational fluid dynamic model in which the flow was assumed to be laminar and adiabatic. The effects of viscous dissipation and vapour generation within the fluid film are fully accounted for by applying a fourth order Runge-Kutta routine to satisfy the radial and filmwise transverse constraints of momentum, energy and mass conservation. The results indicate that the radial velocity profile remains parabolic while the flow remains in the liquid phase and that the radial rate of enthalpy generation is then constant across the film at a given radius. The results also show that evaporation will commence at a radial location determined by geometry and flow conditions and in fluid layers adjacent to the solid boundaries. Evaporation is shown to progress in the radial direction and the load carrying capacity of such a bearing is reduced significantly. Expressions for the viscosity of the liquid/vapour mixture found in the literature survey have not been tested against experimental data. A new formulation is proposed in which the suitable choice of a characteristic constant yields close representation to any of these expressions. Operating constraints imposed by the design of the experimental apparatus limited the extent of the surface over which evaporation could be obtained, and prevented clear identification of the most suitable relationship for the viscosity of the liquid/vapour mixture. The theoretical model was extended to examine the development of two phase flow in a rotating shaft face seal of uniform thickness. Previous theoretical analyses have been based on the assumption that the radial velocity profile of the flow is always parabolic, and that the tangential component of velocity varies linearly from the value at the rotating surface, to zero at the stationary surface. The computational fluid dynamic analysis shows that viscous shear and dissipation in the fluid adjacent to the rotating surface leads to developing evaporation with a consequent reduction in tangential shear forces.

In Ghana, a country with an expanding population and high potential for economic growth, agriculture is an important resource; however, most of the crop production is restricted to low technology shifting cultivation agriculture. The high intensity seasonal rainfall coincides with the early growing period of many of the crops meaning that plots are very susceptible to erosion, especially on steep sided valleys in the region south of Lake Volta. This research investigated the processes of soil erosion by rainfall with the aim of producing a sediment yield model for a small semi-agricultural catchment in rural Ghana. Various types of modelling techniques were considered to discover those most applicable to the sub-tropical environment of Southern Ghana. Once an appropriate model had been developed and calibrated, the aim was to look at how to enable the scaling up of the model using sub-catchments to calculate sedimentation rates of Lake Volta. An experimental catchment was located in Ghana, south west of Lake Volta, where data on rainstorms and the associated streamflow, sediment loads and soil data (moisture content, classification and particle size distribution) was collected to calibrate the model. Additional data was obtained from the Soil Research Institute in Ghana to explore calibration of the Universal Soil Loss Equation (USLE, Wischmeier and Smith, 1978) for Ghanaian soils and environment. It was shown that the USLE could be successfully converted to provide meaningful soil loss estimates in the Ghanaian environment. However, due to experimental difficulties, the proposed theory and methodology of the sediment yield model could only be tested in principle. Future work may include validation of the model and subsequent scaling up to estimate sedimentation rates in Lake Volta.