The general aim of Master’s thesis was to analyze a water supply network in the village Klobouky u Brna using the WaterRisk software through the simple and complex methodology. It was performed a measurement of turbidity on water supply network as practical support of undesirable states. Also it was accomplished detailed exploration of the village Klobouky u Brna. Added value of Master’s thesis was a consultation related to a water supply and a water treatment system with technician working for the Vodovody a kanalizace Hodonín company wherefrom water is bought for the village Klobouky u Brna.

The master’s thesis discusses siphon pipes that are used to collect groundwater. The goal of work is to define the most frequent undesired events that may appear on siphon pipes, and verifying the individual springs. The work is addressed in accordance with the metodology of risk analysis WaterRisk. The content of the work is a summary of the hydraulic of siphon pipes and their use in practice, hazard identification, defining the most frequent undesired events and consequences on siphon pipes, and their verification in the spring in a particular case study.

The goal of the master´s thesis is to approach the isue of risk of investment projects and to deal with situations regarding these risks. The thesis describe the types of risks, their classification, methods of their identification, analysis, and their subsequent processing. In the practical part there will be clearly shown how the influence of some risks can affect the project and its cash flows. The subject of illustrative application is the Aquapark project in Uherské Hradiště.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20344号 / 工博第4281号 / 新制||工||1663(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 白土 博通, 教授 八木 知己, 教授 KIM Chul-Woo, 教授 杉浦 邦征 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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京都大学 / 新制・論文博士 / 博士(工学) / 乙第13492号 / 論工博第4201号 / 新制||工||1785(附属図書館) / (主査)教授 米田 稔, 教授 高野 裕久, 教授 松井 康人 / 学位規則第4条第2項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

This thesis examines two possible orders of combining multiple experts in elicitations with multiple de-composed events: Should experts be combined early or later in the decision process? This thesis is in conjunction with the paper (Baker & Olaleye, 2012) where we show that it is best to combine experts early as later combination leads to a systematic error. We conduct a simulation to more fully flesh out the theoretical model. We also conduct a theoretical analysis aimed at determining how significantly these two methods differ. We find that all results are in accordance with the theory but combining experts later might lead to less error in some cases due to randomness. We then conduct an empirical evaluation of the two methods using data from a previous study. We show that the experts exhibit some form of correlation. The impact of using the two methods of combining experts is then evaluated using an optimal R&D investment portfolio model. We find that the elicitation inputs have a significant effect on the outcome of the optimal portfolio and that there is an advantage from combining experts early.

Climate change is posing significant threats to human beings. Deploying renewable energy sources in electricity generation is widely accepted as an indispensable part of the solution to climate change. The vast potential lies in variable renewable energy sources, such as solar and wind. However, the intermittency of variable renewable energy sources is limiting their deployment. Investing in grid-scale battery systems is a potential solution to this problem. This thesis investigates this potential for the Nordic power sector, taking into account its distinct features, e.g., the vast amount of hydro reservoirs. Taking the capacities of variable renewable energy and battery systems as endogenous variables while considering the salient characteristics of the Nordic power sector, this thesis answers the following research question: How could variable renewable energy investment be supported by complementary investment in grid-scale battery systems to maximise social welfare? Answering this question helps solve the unaddressed research problem of assessing endogenous investment decisions in the capacities of variable renewable energy generation and grid-scale battery systems in the Nordic power market. This, in turn, helps informed decision-making in renewable-energy and energystorage investments to facilitate the realisation of the climate goal. Two experiments are conducted: one with ordinary BESS costs estimation and another assuming a lower-end level of costs. The data come from documents from official statistics (e.g., those from Nord Pool) and peer-reviewed publications. A quadratic programming optimisation model is used to maximise social welfare. Problem instances are then solved using the CPLEX solver implemented in the GAMS software. The results suggest that investing in BESS capacity helps to promote VRE adoption and VRE generation. Consequently, CO2 emission is reduced, and consumer surplus is improved, whereas the total social welfare remains unaffected.

Recently, various self-driving and driving assistance systems such as Advanced Driver Assistance System (ADAS) have been developed with the intent to reduce the number of motor vehicle accidents. While self-driving systems have been proven to reduce traffic accidents, the systems sometimes make other drivers confused because of their mechanical behavior. To avoid confusion and possible error, it is necessary to construct self-driving systems that exhibit human-like behaviors. Risk Potential theory has been used to construct models that successfully represent driver behavior, especially expert behavior. This project uses Risk Potential theory to construct and evaluate a collision avoidance driver model which uses braking to avoid potential collisions with pedestrians. As a first step, a basic driver model which uses Risk Potential theory is constructed and evaluated using metrics such as collision avoidance, comfortability, and false alarm avoidance. Second, human driving data is collected to observe driver’s risk perception during interactions with a pedestrian. Finally, our proposed driver models improve on standard RP model’s performance but comparisons of the models with observed human performance reveal opportunities for further improvement.

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