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<p>In the next few decades, the nuclear industry worldwide is expected to launch a set of reactors with advanced reactor designs. Generation-IV (GEN-IV) reactors are to display superior safety by incorporating additional passive safety concepts as well as improving accident management and minimization of consequences. Canada is in the early stages of conceiving its GEN-IV reactor design – the Supercritical Water Reactor (SCWR). The proposed design is based on the existing CANDU configurations and is expected to offer significant advances in thermal efficiency, fuel cycle sustainability, and relative cost of energy. Of particular interest is the reactor's ability to use inherent or passive safety concepts which will translate to the reactor being walk-away safe in an accident.</p> <p>Steam generators in CANDU remove decay heat by thermosyphoning in a loss of Class-IV power accident. This natural circulation process was a passive feature in GEN-II and GEN-III CANDUs. The SCWR's direct thermodynamic cycle implies steam generators are no longer incorporated into the design. This thesis examines how the SCWR compensates for the removal of a passive safety system element and the difference to the overall safety of the reactor following accidents. These results will be compared to the traditional CANDU's response in accidents to demonstrate the added value of this new reactor in maintaining the goal of no widespread core damage. Comparisons were also made between the SCWR and similar GEN-IV reactors in terms of design and response to various initiating events.</p> <p>Probabilistic Risk Analysis is used in this thesis to assess the SCWR design options. Although the SCWR is in the pre-conceptual design phase, the results of such risk assessment studies could affect the design, operation, and licensing of this new reactor. Future studies can build on this work to conduct more detailed analyses to characterise the SCWR's safety and reliability.</p> / Master of Applied Science (MASc)

Tunnelling in urban areas is one of the most challenging engineering activities, as it has relatively high “risk” due to various uncertainties and the intensity of the possible consequences. Numerous studies have been conducted to address the tunnelling risk, by mainly focusing on the “identification” of the causes and how to control or mitigate the risks. However, limited work has been done on how to quantify the risk by considering the multi-level uncertainties encountered in different phases of the project. The primary objective of this work is to develop a multi-scale risk management (RM) framework to address and quantify the risk of ground surface settlement, induced by tunnelling, in soft clay in urbanized areas. The specific focus is placed on quantifying the risk of tunnel-induced settlement for existing buildings, by taking into account multiple uncertainty levels (e.g. uncertainties of parameters, uncertainties of models, etc.). The framework addresses the tunnel-induced settlement risk, both during the construction of the tunnel as well as after its completion, for buildings with shallow and deep foundations. It offers different classes of assessment to quantify the risk, according to the structure’s current condition and the corresponding limit-state function, that is designated to each class. The RM framework is aligned with ISO 31000 risk management act, consisting of “risk identification”, “risk analysis” and “risk evaluation”. Risk identification includes studies on tunnelling technical reports, field observations, etc., in order to identify the causes of short-term and long-term tunnelling-induced settlement. The risk analysis involves a series of fault tree, event tree and consequence tree analyses to estimate the likelihood of the ground subsidence and subsequent events. For risk evaluation, different probabilistic methods (e.g. first-order reliability method, second-order reliability method and Monte Carlo sampling) are utilized to estimate the risk of surface buildings with shallow and deep foundations. The framework has been implemented in an example problem, to demonstrate the procedure and to address the main influential parameters in each class of assessment using the alpha importance measure. Rt risk tool has been utilized to perform reliability calculations and FORM has been used as the primary method due to its valuable balance between computational cost and accuracy. The outcomes of this RM framework are risk registers and colour-coded risk maps including the exceedance probability of a predefined settlement threshold for each building in the affected area. This framework receives technical data and provides risk-based information for higher-level managers and decision-makers to prioritize their actions and allocate their resources in the most effective way. / Thesis / Master of Applied Science (MASc) / The aim of this study is to provide a multi-level risk management (RM) framework to address and quantify the risk of surface building settlement induced by tunnelling in soft clay in urbanized areas. The focused is placed on quantifying the risk of tunnel-induced settlement of existing buildings, by taking into account multiple uncertainty levels. The framework addresses the tunnel-induced settlement risk, both during the construction of the tunnel as well as after its completion, for buildings with shallow and deep foundations. It offers different classes of assessment to quantify the risk, according to the structure’s current condition and with respect to specific limit-state functions designated for each class. The proposed framework was implemented in an example to demonstrate the procedure and outcomes.

<p dir="ltr">Modern space missions like Mars Sample Return and Artemis involve multiple systems that serve different functions. The individual failure modes of the constituent systems coupled with the complex interdependencies among them can result in various combinations of failures or disruptions that may have an unpredictable impact on the mission. Existing methods of risk assessment are unable to adequately represent the interactions between systems and the progressive consequences of total or partial disruptions for these complex missions. Therefore, a state-based framework has been developed for the probabilistic risk assessment of multi-system uncrewed space exploration missions. This hierarchical framework leverages Harel statecharts to model the operations and failure modes of individual systems. Each failure mode can be characterized by its probability of occurrence and primary consequence (delay in operations, additional cost, fatal failure, etc.). The system-level statecharts are contained within a mission-level model that connects them through logical and temporal operators to simulate functional dependencies among the systems. The double-layer (system-level and mission-level) model can be used for stochastic analysis through Monte Carlo simulations. By defining mission-level performance metrics and observing them for various mission profiles, the system-level operational risks can be related to the mission outcomes, and the mission-level impact of each failure mode can be assessed. Overall, this framework can provide deeper and richer insights by enabling sensitivity analysis, risk quantification/ranking, and comparison of various operational concepts and mission architectures. The framework has been demonstrated for three types of analyses within the Mars Sample Return Campaign.</p>

Idag används affärssystem inom de flesta verksamheter. Syftet med att använda sig av ett affärssystem är att det ska stödja verksamhetens handlingar och bidra till effektivitet inom organisationen. I dagens läge har de flesta verksamheter infört eller tänkt införa/byta ut ett affärssystem vilket ibland inte är så lätt. Införandet och användandet av ett affärssystem kan potentiellt leda till många förändringar. Jag kommer att med denna studie påvisa vilka faktorer verksamheter behöver ha med sig för att lyckas med ett affärssystemsinförande men samtidigt ta upp vilka fallgropar man ska se sig för vid införandet. Detta för att göra införandet så smidigt som möjligt och inte leda till för många ”dåliga” förändringar.För att få svar på detta har jag baserat min uppsats på teoretiskt och empiriskt material. Jag har utgått från existerande teorier och relaterat dessa till mitt empiriska underlag. Den information jag samlar in har jag fått genom två intervjuer av företag som är i ett skede att införa ett nytt affärssystem samtidigt som jag underbyggt dessa intervjuer med relevant teori.Till viss del går denna studie att generalisera men jag ser denna studie mer som ett riktmärke till företag som ska eller har funderat på att byta ut eller införa ett affärssystem.

In order to prevent power system blackout, and enhance system reliability, various forms of special protection systems (SPS) and defense plans have been implemented by utilities around the world. One of the main concerns in the design of an SPS is to assure whether the system could fit with the reliability specification requirements. The failure of SPS to detect the defined conditions and carry out the required actions, or to take unnecessary actions, could lead to serious and costly consequences. Thus, a quantitative reliability assessment for SPS is important and necessary. Using a single point value for the parameter to evaluate the reliability of SPS might give incomplete information about the system reliability due to the uncertainty of reliability model and input data. When a review study suggests that some modifications of the existing scheme are necessary, the sensitivity analysis techniques could provide the tools to do this investigation to identify the most significant components that have essential effects on the reliability of the SPS. In this dissertation, by incorporating an interval theory, a risk reduction worth importance concept, and a probabilistic risk-based index, a procedure is proposed to conduct parameter uncertainty analysis, identify critical factors in the reliability model, perform probabilistic risk assessments (PRA) and determine a better option for the refinement of the studied SPS decision process logic module. One of the existing SPSs of Taipower systems is used to illustrate the practicability and appropriation of the proposed design refinement procedure. With the advent of deregulation in the power industry, utilities have experienced a great pressure to fully utilize their current facilities to the maximum level. SPSs are often considered as a cost effective way in achieving this goal. This dissertation also presents a framework for quantitative assessment of the benefits and risks due to SPS implementation. Changes in energy, spinning reserve and customer interruption costs resulting from SPS operations are evaluated and risks of SPS operations and system security are assessed. The proposed methodologies are useful for power system planners and operators to evaluate the value and effectiveness of SPS for the remedy of transmission congestion and reliability problems.

L'étude probabiliste de sûreté (EPS) parasismique est l'une des méthodologies les plus utiliséespour évaluer et assurer la performance des infrastructures critiques, telles que les centrales nucléaires,sous excitations sismiques. La thèse discute sur les aspects suivants: (i) Construction de méta-modèlesavec les réseaux de neurones pour construire les relations entre les intensités sismiques et les paramètresde demande des structures, afin d'accélérer l'analyse de fragilité. L'incertitude liée à la substitution desmodèles des éléments finis par les réseaux de neurones est étudiée. (ii) Proposition d'une méthodologiebayésienne avec réseaux de neurones adaptatifs, afin de prendre en compte les différentes sourcesd'information, y compris les résultats des simulations numériques, les valeurs de référence fournies dansla littérature et les évaluations post-sismiques, dans le calcul de courbes de fragilité. (iii) Calcul des loisd'atténuation avec les réseaux de neurones. Les incertitudes épistémiques des paramètres d'entrée de loisd'atténuation, tels que la magnitude et la vitesse moyenne des ondes de cisaillement de trente mètres, sontprises en compte dans la méthodologie développée. (iv) Calcul du taux de défaillance annuel en combinantles résultats des analyses de fragilité et de l'aléa sismique. Les courbes de fragilité sont déterminées parle réseau de neurones adaptatif, tandis que les courbes d'aléa sont obtenues à partir des lois d'atténuationconstruites avec les réseaux de neurones. Les méthodologies proposées sont appliquées à plusieurs casindustriels, tels que le benchmark KARISMA et le modèle SMART. / Seismic probabilistic risk assessment (SPRA) is one of the most widely used methodologiesto assess and to ensure the performance of critical infrastructures, such as nuclear power plants (NPPs),faced with earthquake events. SPRA adopts a probabilistic approach to estimate the frequency ofoccurrence of severe consequences of NPPs under seismic conditions. The thesis provides discussionson the following aspects: (i) Construction of meta-models with ANNs to build the relations betweenseismic IMs and engineering demand parameters of the structures, for the purpose of accelerating thefragility analysis. The uncertainty related to the substitution of FEMs models by ANNs is investigated.(ii) Proposal of a Bayesian-based framework with adaptive ANNs, to take into account different sourcesof information, including numerical simulation results, reference values provided in the literature anddamage data obtained from post-earthquake observations, in the fragility analysis. (iii) Computation ofGMPEs with ANNs. The epistemic uncertainties of the GMPE input parameters, such as the magnitudeand the averaged thirty-meter shear wave velocity, are taken into account in the developed methodology.(iv) Calculation of the annual failure rate by combining results from the fragility and hazard analyses.The fragility curves are determined by the adaptive ANN, whereas the hazard curves are obtained fromthe GMPEs calibrated with ANNs. The proposed methodologies are applied to various industrial casestudies, such as the KARISMA benchmark and the SMART model.

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Risk assessment is essential for nuclear power plants (NPPs) due to the complex dynamic nature of such systems-of-systems, as well as the devastating impacts of nuclear accidents on the environment, public health, and economy. Lessons learned from the Fukushima nuclear accident demonstrated the importance of enhancing current risk assessment methodologies and developing efficient early warning decision support tools. Static probabilistic risk assessment (PRA) techniques (e.g., event and fault tree analysis) have been extensively adopted in nuclear applications to ensure NPPs comply with safety regulations. However, numerous studies have highlighted the limitations of static PRA methods such as the lack of considering the dynamic hardware/software/operator interactions inside the NPP and the timing/sequence of events. In response, several dynamic probabilistic risk assessment (DPRA) methodologies have been developed and continuously evolved over the past four decades to overcome the limitations of static PRA methods. DPRA presents a comprehensive approach to assess the risks associated with complex, dynamic systems. However, current DPRA approaches are faced with challenges associated with the intra/interdependence within/between different NPP complex systems and the massive amount of data that needs to be analyzed and rapidly acted upon. In response to these limitations of previous work, the main objective of this dissertation is to develop a physics-based DPRA platform and an intelligent data-driven prediction tool for NPP safety enhancement under normal and abnormal operating conditions. The results of this dissertation demonstrate that the developed DPRA platform is capable of simulating the dynamic interaction between different NPP systems and estimating the temporal probability of core damage under different transients with significant analysis advantages from both the computational time and data storage perspectives. The developed platform can also explicitly account for uncertainties associated with the NPP's physical parameters and operating conditions on the plant's response and probability of its core damage. Furthermore, an intelligent decision support tool, developed based on artificial neural networks (ANN), can significantly improve the safety of NPPs by providing the plant operators with fast and accurate predictions that are specific to such NPP. Such rapid prediction will minimize the need to resort to idealized physics-based simulators to predict the underlying complex physical interactions. Moving forward, the developed ANN model can be trained under plant operational data, plants operating experience database, and data from rare event simulations to consider for example plant ageing with time, operational transients, and rare events in predicting the plant behavior. Such intelligent tool can be key for NPP operators and managers to take rapid and reliable actions under abnormal conditions. / Thesis / Doctor of Philosophy (PhD)

The current thesis focuses on estimating the damage levels and evaluating the out-of-plane behavior of fully-grouted reinforced masonry (RM) structural walls under blast loading, a load that they are typically not designed to resist. Twelve third-scale RM walls were constructed and tested under free-field blast tests. Three different reinforcement ratios and three different charge weights have been used on the walls, with scaled distances down to 1.7 m/kg1/3 and two different boundary conditions, to evaluate the walls’ performances. In general, the results show that the walls are capable of withstanding substantial blast load levels with different extents of damage depending on their vertical reinforcement ratio and scaled distance. It worth mention that the current definitions of damage states, specified in ASCE/SEI 59-11 (ASCE 2011) and CAN/CSA S850-12 (CSA 2012) standards, involve global response limits such as the component support rotations that are relatively simple to calculate. However, these quantitative damage state descriptors can be less relevant for cost–benefit analysis. Moreover, the reported experimental results showed that the use of quantitative versus qualitative damage descriptors specified by North American blast standards [ASCE 59-11 (ASCE 2011) and CSA S850-12 (CSA 2012)] can result in inconstancies in terms of damage state categorization. Therefore, revised damage states that are more suitable for a cost–benefit analysis, including repair technique and building downtime, were presented. These damage states are currently considered more meaningful and have been used to quantify the post-earthquake performance of buildings. In addition, a nonlinear single-degree-of-freedom (SDOF) model is developed to predict the out-of-plane behavior of RM structural walls under blast loading. The proposed SDOF model is first verified using quasi-static and free-field blast tests and then subsequently used to extend the results of the reported experimental test results with different design parameters such as threat level, reinforcement ratio, available block width, wall height, and material characteristics. In general, brittle behavior was observed in the walls with a reinforcement ratio higher than 0.6%. This is attributed to the fact that seismically detailed structural masonry walls designed to respond in a ductile manner under in-plane loads might develop brittle failure under out-of-plane loads because of their reduced reinforcement moment arm. In addition, increased ductility can be achieved by using two reinforcement layers instead of a single layer, even if the reinforcement ratio is reduced. Also, it is recommended to consider the use of larger concrete masonry blocks for the construction of RM structural walls that are expected to experience blast loads in order to reduce the slenderness ratio and for the placement of two reinforcement layers. Finally, a probabilistic risk assessment (PRA) framework is proposed in order to develop design basis threat (DBT) fragility curves for reinforced concrete block shear wall buildings, which can be utilized to meet different probabilities of failure targets. To illustrate the proposed methodology, an application is presented involving a medium–rise reinforced masonry building, under different DBT levels. The DBT fragility curves are obtained via Monte Carlo sampling of the random variables and are used to infer the locations, within the building premises, that are most suitable for the erection of barriers for blast hardening. / Thesis / Doctor of Philosophy (PhD)