Safety systems are designed to prevent the occurrence of certain conditions and their future development into a hazardous situation. The consequence of the failure of a safety system of a potentially hazardous industrial system or process varies from minor inconvenience and cost to personal injury, significant economic loss and death. To minimise the likelihood of a hazardous situation, safety systems must be designed to maximise their availability. Therefore, the purpose of this thesis is to propose an effective safety system design optimization scheme. A multi-objective genetic algorithm has been adopted, where the criteria catered for includes unavailability, cost, spurious trip and maintenance down time. Analyses of individual system designs are carried out using the latest advantages of the fault tree analysis technique and the binary decision diagram approach (BDD). The improved strength Pareto evolutionary approach (SPEA2) is chosen to perform the system optimization resulting in the final design specifications. The practicality of the developed approach is demonstrated initially through application to a High Integrity Protection System (HIPS) and subsequently to test scalability using the more complex Firewater Deluge System (FDS). Computer code has been developed to carry out the analysis. The results for both systems are compared to those using a single objective optimization approach (GASSOP) and exhaustive search. The overall conclusions show a number of benefits of the SPEA2 based technique application to the safety system design optimization. It is common for safety systems to feature dependency relationships between its components. To enable the use of the fault tree analysis technique and the BDD approach for such systems, the Markov method is incorporated into the optimization process. The main types of dependency which can exist between the safety system component failures are identified. The Markov model generation algorithms are suggested for each type of dependency. The modified optimization tool is tested on the HIPS and FDS. Results comparison shows the benefit of using the modified technique for safety system optimization. Finally the effectiveness and application to general safety systems is discussed.

The focus of this thesis is to develop a generic approach for solving reliability design optimisation problems which could be applicable to a diverse range of real engineering systems. The basic problem in optimal reliability design of a system is to explore the means of improving the system reliability within the bounds of available resources. Improving the reliability reduces the likelihood of system failure. The consequences of system failure can vary from minor inconvenience and cost to significant economic loss and personal injury. However any improvements made to the system are subject to the availability of resources, which are very often limited. The objective of the design optimisation problem analysed in this thesis is to minimise system unavailability (or unreliability if an unrepairable system is analysed) through the manipulation and assessment of all possible design alterations available, which are subject to constraints on resources and/or system performance requirements. This thesis describes a genetic algorithm-based technique developed to solve the optimisation problem. Since an explicit mathematical form can not be formulated to evaluate the objective function, the system unavailability (unreliability) is assessed using the fault tree method. Central to the optimisation algorithm are newly developed fault tree modification patterns (FTMPs). They are employed here to construct one fault tree representing all possible designs investigated, from the initial system design specified along with the design choices. This is then altered to represent the individual designs in question during the optimisation process. Failure probabilities for specified design cases are quantified by employing Binary Decision Diagrams (BDDs). A computer programme has been developed to automate the application of the optimisation approach to standard engineering safety systems. Its practicality is demonstrated through the consideration of two systems of increasing complexity; first a High Integrity Protection System (HIPS) followed by a Fire Water Deluge System (FWDS). The technique is then further-developed and applied to solve problems of multi-phased mission systems. Two systems are considered; first an unmanned aerial vehicle (UAV) and secondly a military vessel. The final part of this thesis focuses on continuing the development process by adapting the method to solve design optimisation problems for multiple multi-phased mission systems. Its application is demonstrated by considering an advanced UAV system involving multiple multi-phased flight missions. The applications discussed prove that the technique progressively developed in this thesis enables design optimisation problems to be solved for systems with different levels of complexity. A key contribution of this thesis is the development of a novel generic optimisation technique, embedding newly developed FTMPs, which is capable of optimising the reliability design for potentially any engineering system. Another key and novel contribution of this work is the capability to analyse and provide optimal design solutions for multiple multi-phase mission systems. Keywords: optimisation, system design, multi-phased mission system, reliability, genetic algorithm, fault tree, binary decision diagram

We examine the evolution of globular star clusters, modelled as spherically symmetric stellar systems, using various techniques. Such clusters possess a central region of approximately uniform density which is referred to as the core. We concentrate our analysis on the evolution of the cluster after the core has undergone core collapse; a process where its radius decreases and its density increases. After this collapse, the system as a whole can expand in a self-similar fashion (homologous post-collapse evolution) which has long been thought to be due to gravitational interactions between different populations of single stars and binary stars in the core. We confirm this assumption by constructing a simple analytical model which combines much of the theoretical knowledge of previous research in the field. This model consists of two stellar populations, each defined by the mass of the individual stars, and a separate core. Our simple model is itself constructed from two simpler models – a twocomponent model without a core and a single mass model with a core – and takes into account the main gravitational interactions thought to drive the post-collapse evolution. To ensure that no important mechanisms have been neglected in our simple model, we will compare it with an N-body simulation. We compute our N-body models with NBODY6 (using a GPU version for large N). When we compare the N-body model with the simple model, we find qualitative agreement between them for most cases. Even though some mechanisms (e.g. escape of stars) are neglected in our simple model, we find that both models show homologous post-collapse evolution. We also review the homologous post-collapse Fokker-Planck model in the case of equal stellar masses derived by H´enon (1961) with the intention of extending this for the two-component case. We present our numerical solutions for H´enon’s model and find that our numerical solutions are in satisfactory agreement with the results shown in this paper. When we extend this work for a general two-component model (i.e. with no restriction on the number of heavier stars), we find that a homologous solution cannot be found with this approach. By contrast, we suggest that it would be possible to find a homologous two-component solution by extending the one-component solution published later by H´enon (1965), which differs from the earlier model by neglecting the external tidal field of the parent galaxy. Much of the work shown in this thesis would be relevant for such future study.

Very long and noisy sequence data arise from biological sciences to social science including high throughput data in genomics and stock prices in econometrics. Often such data are collected in order to identify and understand shifts in trends, for example, from a bull market to a bear market in finance or from a normal number of chromosome copies to an excessive number of chromosome copies in genetics. Thus, identifying multiple change points in a long, possibly very long, sequence is an important problem. In this article, we review both classical and new multiple change-point detection strategies. Considering the long history and the extensive literature on the change-point detection, we provide an in-depth discussion on a normal mean change-point model from aspects of regression analysis, hypothesis testing, consistency and inference. In particular, we present a strategy to gather and aggregate local information for change-point detection that has become the cornerstone of several emerging methods because of its attractiveness in both computational and theoretical properties.

The overall aim was to study transgender persons’ experiences of, and reactions upon, attitudes and social norms in relation to their gender identity. Another question that was relevant to answer was how transgender persons are affected by the hetero norm. The method used to collect data was through questionnaires published on the internet. The only requirement to participate was to be a transgender over 18 years old, and when the survey closed, 35 respondents had answered it. The questionnaire consisted of both quantitative and qualitative questions. Collected data were analyzed using descriptive statistics and content analysis. The results indicate that transgender persons living conditions are largely affected by norms, and that they encounter a considerable amount of negative attitudes due to their gender identity. To "pass" as either man or woman turned out to be something that made it easier for transgender people to evade negative attitudes. One hope is that this study can provide knowledge to different instances in the community to open up to be more open to critical thinking around norms. The conclusion was that persons with a transgender identity are affected by societal norms and by heteronormativity. It takes a lot of courage to be able to be one self but everything boils down to how strong a person are and the availability of support and role models in the surrounding society. / Studiens övergripande syfte var att studera transpersoners erfarenheter av, och reaktionerpå, omgivningens attityder samt samhällets normer i relation till deras könsidentitet. Ytterligare en fråga som var relevant att besvara var hur deras liv påverkas av heteronormen. Forskning kring transpersoner och hur de påverkas av normer och det omgivande samhället är relativt begränsat vilket var en av anledningarna till valet av ämne. Data samlades in genom enkäter publicerade på webben där 35 respondenter svarade. Kriterierna för att delta var att man var transperson och över 18 år. Svaren som kom in var från transpersoner spridda i Sverige. Enkäten bestod av både kvantitativa och kvalitativa frågor. Majoriteten av frågorna hade hämtats från Folkhälsomyndighetens frågeformulärriktat till transpersoner. Insamlat material har analyserats med hjälp av beskrivande statistik samt innehållsanalys. Resultatet tyder på att transpersoners livsvillkor i stor utsträckning påverkas av normer samt att de får utstå en hel del negativt bemötande på grund av sin könsidentitet. Att ”passera” som antingen man eller kvinna visade sigvara något som gör det enklare för transpersoner att undvika negativt bemötande. Kränkande behandling kom vanligast från främlingar och personer på internet. Negativt bemötande var något som respondenterna var vana vid och många berättade om händelser i vården där de blivit negativt bemötta av personalen. En förhoppning är att detta arbete kan bidra till att sprida kunskap till människor inom olika instanser i samhället för att öppna upp för ett mer normkritiskt perspektiv. Slutsatsen blev att transpersoner i stor utsträckning påverkas av normer och av det omgivande samhället. Dock beror mycket på hur stark man är som person, vilka förebilder som finns och hur mycket stöd man får från omgivningen.

This thesis presents a unique design for an infrared spectrometer based on a MEMS Binary Fresnel Zone Plate for the purpose of assessing the health of oil-impregnated high voltage (HV) equipment. It does so by measuring dissolved gases within it. These gases include carbon monoxide, carbon dioxide, methane, ethane, ethylene, and acetylene. These gases are currently measured using numerous technologies such as gas combustion, gas chromatography, photoacoustic spectroscopy, and FTIR spectroscopy. Each of these technologies have their advantages and disadvantages. The design presented in this thesis consists of an analysis of how the various Binary Zone Plate parameters affect its spectral resolution and transmission efficiency. Simulations show that increasing the number of zones and the focal length, as well as decreasing the aperture diameter, increases the spectral resolution of the spectrometer. Simulations also show that transmission efficiency is proportional to the number of zones and the aperture diameter. This thesis presents a theoretical argument for how one zone plate lens can be used to measure all dissolved gases present in HV equipment. Lenses for the visible and infrared ranges were fabricated in the University of Manitoba NSFL Cleanroom. The lenses were then tested in an optical setup. The results show that the visible light experiments were successful in achieving appropriate spectral discrimination by changing the distance between the aperture and the lens. The results from the infrared experiment show that a detector was able to discriminate between full and no incident radiation. / May 2017

We report on a search for short -period binary systems composed of pairs of evolved stars. The search is being carried out concurrently with a program to characterize the kinematical properties of two different samples of stars. Each sample has produced one close binary candidate for which further spectroscopic observations are planned. We also recapitulate the discovery of a close detached binary system composed of two cool DA white dwarfs, and we discuss the null results of Ha observations of the suspected white dwarf /brown dwarf system G 29-38.

The optimal design of geothermal power plants across the entire spectrum of meaningful geothermal brine temperatures and climates is investigated, while accounting for vital real-world constraints that are typically ignored in the existing literature. The constrained design space of both double-flash and binary geothermal power plants is visualized, and it is seen that inclusion of real-world constraints is vital to determining the optimal feasible design of a geothermal power plant. The effect of varying condenser temperature on optimum plant performance and optimal design specifications is analyzed. It is shown that condenser temperature has a significant effect on optimal plant design as well. The optimum specific work output and corresponding optimal design of geothermal power plants across the entire range of brine temperatures and condenser temperatures is illustrated and tabulated, allowing a scientifically sound assessment of both feasibility and appropriate plant design under any set of conditions. The performance of genetic algorithms and particle swarm optimization are compared with respect to the constrained, non-linear, simulation-based optimization of a prototypical geothermal power plant, and particle swarm optimization is shown to perform significantly better than genetic algorithms. The Pareto-optimal front of specific work output and specific heat exchanger area is visualized and tabulated for binary and double-flash plants across the full range of potential geothermal brine inlet conditions and climates, allowing investigation of the specific trade-offs required between specific work output and specific heat exchanger area. In addition to the novel data, this dissertation research illustrates the development and use of a sophisticated analysis tool, based on multi-objective particle swarm optimization, for the optimal design of geothermal power plants.

In some situations we cannot observe the original time series and instead, we record only binary data which express whether the values of the original series exceeded a certain threshold or not. The thesis deals with estimation of characteristics of the original series constructed from the binary (so called clipped or hard-limited) data, in particular in Gaussian ARMA models. We summarize some basic characteristics of the clipped series and describe their relation to the original ones. Some practical examples are provided as well. The estimation of parameters in AR(p) model is shown for the case of zero threshold. Using a similar approach, an estimator of the MA(1) model parameter is proposed and its properties are studied with emphasis on asymptotic variance. Subsequently, we propose an estimation procedure for AR(p) and MA(1) models with unknown (non-zero) threshold. The behaviour of our estimators is investigated in a simulation study, which provides a comparison with estimators constructed from the original data. Finally, a real data analysis is presented for an illustration. Powered by TCPDF (www.tcpdf.org)

New CCD photometric observations of ten short-period LMB (Low Mass Binaries) were carried out. Data were obtained using 65 cm telescope in Ondřejov in the filters I, R and V from 2014 to 2016. Light curves were analysed using the program PHOEBE. The obtained masses and radii of the stars were compared with the theoretical mass-radii relation. There arises that the short-period binaries have the radii of about 4 % larger than the theoretical prediction from the stellar evolution models. Powered by TCPDF (www.tcpdf.org)