The prediction of vibration in large electric machines

This thesis reports the development of a reliable method for the prediction of response to electromagnetically induced vibration in large electric machines. The machines of primary interest are DC ship-propulsion motors but much of the work reported has broader significance. The investigation has involved work in five principal areas. (1) The development and use of dynamic substructuring methods. (2) The development of special elements to represent individual machine components. (3) Laboratory scale investigations to establish empirical values for properties which affect machine vibration levels. (4) Experiments on machines on the factory test-bed to provide data for correlation with prediction. (5) Reasoning with regard to the effect of various design features. The limiting factor in producing good models for machines in vibration is the time required for an analysis to take place. Dynamic substructuring methods were adopted early in the project to maximise the efficiency of the analysis. A review of existing substructure- representation and composite-structure assembly methods includes comments on which are most suitable for this application. In three appendices to the main volume methods are presented which were developed by the author to accelerate analyses. Despite significant advances in this area, the limiting factor in machine analyses is still time. The representation of individual machine components was addressed as another means by which the time required for an analysis could be reduced. This has resulted in the development of special elements which are more efficient than their finite-element counterparts. The laboratory scale experiments reported were undertaken to establish empirical values for the properties of three distinct features - lamination stacks, bolted-flange joints in rings and cylinders and the shimmed pole-yoke joint. These are central to the preparation of an accurate machine model. The theoretical methods are tested numerically and correlated with tests on two machines (running and static). A system has been devised with which the general electromagnetic forcing may be split into its most fundamental components. This is used to draw some conclusions about the probable effects of various design features.

Effect of microstructure upon elastic behaviour of human tooth enamel

Tooth enamel is the stiffest tissue in the human body with a well-organized microstructure. Developmental diseases, such as enamel hypomineralisation, have been reported to cause marked reduction in the elastic modulus of enamel and consequently impair dental function. We produce evidence, using site-specific transmission electron microscopy (TEM), of difference in microstructure between sound and hypomineralised enamel. Built upon that, we develop a mechanical model to explore the relationship of the elastic modulus of the mineral-protein composite structure of enamel with the thickness of protein layers and the direction of mechanical loading. We conclude that when subject to complex mechanical loading conditions, sound enamel exhibits consistently high stiffness, which is essential for dental function. A marked decrease in stiffness of hypomineralised enamel is caused primarily by an increase in the thickness of protein layers between apatite crystals and to a lesser extent by an increase in the effective crystal orientation angle. © 2009 Elsevier Ltd. All rights reserved.

Institutions and firm ownership structure:evidence from Central and Eastern Europe

FDI plays a key role in development, particularly in resource-constrained transition economies of Central and Eastern Europe with relatively low savings rates. Gains from technology transfer play a critical role in motivating FDI, yet potential for it may be hampered by a large technology gap between the source and host country. While the extent of this gap has traditionally been attributed to education, skills and capital intensity, recent literature has also emphasized the possible role of institutional environment in this respect. Despite tremendous interest among policy-makers and academics to understand the factors attracting FDI (Bevan and Estrin, 2000; Globerman and Shapiro, 2003) our knowledge about the effects of institutions on the location choice and ownership structure of foreign firms remains limited. This paper attempts to fill this gap in the literature by examining the link between institutions and foreign ownership structures. To the best of our knowledge, Javorcik (2004) is the only papers, which use firm-level data to analyse the role of institutional quality on an outward investor’s entry mode in transition countries. Our paper extends Javorcik (2004) in a number of ways: (a) rather than a cross-section, we use panel data for the period 1997-2006; (b) rather than a binary variable, we use the percentage foreign ownership as continuous variable; (c) we consider multi-dimensional institutional variables, such as corruption, intellectual property rights protection and government stability. We also use factor analysis to generate a composite index of institutional quality and see how stronger institutional environment could affect foreign ownership; (d) we explore how the distance between institutional environment in source and host countries affect foreign ownership in a host country. The firm-level data used includes both domestic and foreign firms for the period 1997-2006 and is drawn from ORBIS, a commercially available dataset provided by Bureau van Dijk. In order to examine the link between institutions and foreign ownership structures, we estimate four log-linear ownership equations/specifications augmented by institutional and other control variables. We find evidence that the decision of a foreign firm to either locate its subsidiary or acquire an existing domestic firm depends not only on factor cost differences but also on differences in institutional environment between the host and source countries.

In vitro hydrolytic degradation of centrifugally spun polyhydroxybutyrate-pectin composite fibres

BACKGROUND: Centrifugal spinning is a novel fibre-forming process that readily permits the incorporation of additives while avoiding the thermal damage often associated with conventional melt spinning. Centrifugal spinning of a viscous solution of poly(3-hydroxybutyrate) (PHB) mixed with pectin was used to fabricate a range of fibres containing different concentrations of this biologically active agent. The influence of this blending on fibre morphology and in vitro degradation in an accelerated hydrolytic model at 70 ?C and pH of 10.6 is reported. RESULTS: Blending influenced the physiochemical properties of the fibres, andthis significantly affected thedegradation profile of both the fibre and its PHB constituent. A greater influence on degradation was exerted by the type of pectin and its degree of esterification than by variations in its loading. CONCLUSION: Centrifugal spinning permits the fabrication of composite fibrous matrices from PHB and pectin. Incorporation of the polysaccharide into the fibres can be used to manipulate degradation behaviour and demonstrates a model for doping of matrices with active biological constituents. The unique features of the centrifugal spinning process, as illustrated by the structure of the fibres and the degradation profiles, suggest possible applications of centrifugally spun biopolymers as wound scaffolding devices and in tissue engineering.

Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

Composite cell support membranes based on collagen and polycaprolactone for tissue engineering of skin

The preparation and characterisation of collagen:PCL composites for manufacture of tissue engineered skin substitutes and models are reported. Films having collagen:PCL (w/w) ratios of 1:4, 1:8 and 1:20 were prepared by impregnation of lyophilised collagen mats by PCL solutions followed by solvent evaporation. In vitro assays of collagen release and residual collagen content revealed an expected inverse relationship between the collagen release rate and the content of synthetic polymer in the composite that may be exploited for controlled presentation and release of biopharmaceuticals such as growth factors. DSC analysis revealed the characteristic melting point of PCL at around 60°C and a tendency for the collagen component, at high loading, to impede crystallinity development within the PCL phase. The preparation of fibroblast/composite constructs was investigated using cell culture as a first stage in mimicking the dermal/epidermal structure of skin. Fibroblasts were found to attach and proliferate on all the composites investigated reaching a maximum of 2×105/cm2 on 1:20 collagen:PCL materials at day 8 with cell numbers declining thereafter. Keratinocyte growth rates were similar on all types of collagen:PCL materials investigated reaching a maximum of 6.6×104/cm2 at day 6. The results revealed that composite films of collagen and PCL are favourable substrates for growth of fibroblasts and keratinocytes and may find utility for skin repair. © 2003 Elsevier Ltd. All rights reserved.

Developing a probabilistic graphical structure from a model of mental-health clinical risk expertise

This paper explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. The Galatean Risk Screening Tool [1] is a psychological model for mental health risk assessment based on fuzzy sets. This paper details how the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. These semantics are formalised by a detailed specification for an XML structure used to represent the expertise. The component parts were then mapped to equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements. © Springer-Verlag 2010.