Nesta tese o autor estabelece um método sistemático de quantificação de risco em obras subterrâneas em maciço rochoso fraturado utilizando de maneira eficiente conceitos de confiabilidade estrutural. O método é aplicado a um caso de estudo real da caverna da Usina Hidrelétrica Paulo Afonso IV, UHE-PAIV. Adicionalmente, um estudo de otimização de projeto com base em risco quantitativo também é apresentado para mostrar as potencialidades do método. A estimativa do risco foi realizada de acordo com as recomendações da Organização de Auxílio contra Desastres das Nações Unidas, UNDRO, onde o risco pode ser estimado como a convolução entre as funções de perigo, vulnerabilidade e perdas. Para a quantificação da confiabilidade foram utilizados os métodos de aproximação FORM e SORM com uso de acoplamento direto e de superfícies de resposta polinomial quadráticas. A simulação de Monte Carlo também foi utilizada para a quantificação da confiabilidade no estudo de caso da UHE-PAIV devido à ocorrência de múltiplos modos de falha simultâneos. Foram avaliadas as ameaças de convergência excessiva das paredes, colapso da frente de escavação e a queda de blocos. As funções de perigo foram estimadas em relação à intensidade da ameaça como razão de deslocamento da parede ou volume do bloco. No caso da convergência excessiva, um túnel circular profundo foi estudado com o intuito de comparar a qualidade de aproximação da técnica numérica (FLAC3D com acoplamento direto) em relação à solução exata. Erros inferiores a 0,1% foram encontrados na estimativa do índice de confiabilidade ß. Para o caso da estabilidade de frente foram comparadas duas soluções da análise limite da plasticidade contra a solução obtida numericamente. Já no caso de queda de bloco, verificou-se que as recomendações de parcialização do sistema de classificação geomecânica Q incrementa consideravelmente a segurança da escavação conduzindo a padrões da prática mais avançada, por exemplo, de um ß de 2,04 para a escavação a seção plena até 4,43 para o vão recomendado. No estudo de caso, a segurança da caverna da UHE-PAIV foi estudada perante a queda de blocos utilizando o software Unwedge. A probabilidade de falha individual foi integrada no comprimento da caverna e o conceito de sistema foi utilizado para estimar a probabilidade de falha global. A caverna apresentou uma probabilidade de falha global de 3,11 a 3,22% e um risco de 7,22x10-3 x C e 7,29x10-3 x C, sendo C o custo de falha de um bloco de grandes dimensões. O bloco mais crítico apresentou um ß de 3,63. No estudo de otimização foram utilizadas duas variáveis de projeto, a espessura do concreto projetado e o número de tirantes por metro quadrado. A configuração ótima foi encontrada como o par [t, nb] que minimiza a função de custo total. Também, um estudo de sensibilidade foi realizado para avaliar as influências de alguns parâmetros no projeto ótimo da escavação. Finalmente, os resultados obtidos sugerem que as análises quantitativas de risco, como base para a avaliação e gestão de risco, podem e devem ser consideradas como diretriz da prática da engenharia geotécnica, uma vez que estas análises conciliam os conceitos básicos de projeto como eficiência mecânica, segurança e viabilidade financeira. Assim, a quantificação de risco é plenamente possível. / In this thesis the author establishes a systematic method for quantifying the risk in underground structures in fractured rock masses using structural reliability concepts in an efficient way. The method is applied to the case study of the underground cavern of Paulo Afonso IV Hydroelectrical Power Station UHE-PAIV. Additionally, an optimization study was conducted in order to show a potential application of the method. The estimation of the risk was done according to the recommendations of the United Nations Disaster Relief Organization UNDRO where risk can be estimated as the convolution between the hazard, vulnerability and losses functions. FORM and SORM were used as approximation methods for the reliability quantification by means of Direct Coupling and Quadratic Polynomial Response Surfaces. A Monte Carlo simulation was also used to quantify the reliability of the cavern UHE-PAIV because of the presence of multiple failure modes in the numerical model. In this study 3 types of threads were evaluated: excessive wall convergence, face stability and wedge block fall. Hazard functions were built relative to the thread intensities such as wall convergence ratio or block size. In the case of excessive wall convergence a deep circular tunnel was studied meaning to compare the quality of the approximation of the reliability technique (FLAC3D with direct coupling) to the exact solution. Errors below 0.1% were found in the reliability index ß estimation. The reliability of the face stability was evaluated using two limit analysis solutions against the numeric estimation. For the block stability it was verified that the sequential excavation recommended by the Q system increases considerably the reliability of the excavation leading safety to modern standard levels, e.g. from a ß equal to 2.04 for a full section excavation to 4.43 for a partial excavation. In the case study of the UHE-PAIV, the reliability of the underground cavern was estimated using the commercial software Unwedge. The probability of failure of individual blocks was integrated along the length of the cavern and the concept of structural system was used to estimate the global probability of failure. The cavern presented a probability of failure of 3.11% to 3.22% and a risk of 7.22x10-3 x C and 7.29x10-3 x C - where C is the cost of failure of a large block. The critical individual block showed a ß equal to 3.63. The optimization was performed considering two design variables − liner thickness and number of bolt per square meter. The optimal design was found as the pair, [t, nb] which minimizes the total cost function. Also, a sensibility analysis was conducted to understand the influence of some parameters in the location of the optimal excavation design. Concluding, the results obtained here suggest that the quantitative risk analyses, as a base for the risk assessment and management, can and must be considered as a north for the practice of geotechnical engineering owing that these analyses reconcile the basic concepts of mechanical efficiency, safety and financial feasibility. Thus, risk quantification is fully affordable.

Cette thèse porte sur la modélisation, la prévision et la couverture du risque de contagion financière. Après une présentation générale des fondements théoriques et des mécanismes de propagation relatifs à la contagion financière, nous introduisons une modélisation fondée sur les modèles de cointégration non linéaire et de causalité non linéaire dans lesquels, les variables et le terme d’erreur du modèle à correction d’erreur obéissent à la dynamique de processus auto-régressifs à changement de régime de type TAR et M-TAR pour capter l’effet de contagion. Une extension de cette modélisation au cadre de prévision probabiliste conditionnelle a été faite par la suite à travers les réseaux de croyance Bayésienne pour renforcer le pouvoir prédictif. Ensuite, nous montrons comment une institution financière peut couvrir son portefeuille contre ce type de risque par de nouvelles approches. Nous proposons pour cela, une stratégie de couverture purement statique dans une perspective règlementaire à l’aide de modèles génératifs de type Vines-copula, une stratégie de couverture semi-statique fondée sur la budgétisation des risques et une stratégie de couverture dynamique à partir des processus de diffusion à sauts mutualisés. Ces nouvelles modélisations sont testées empiriquement sur un ensemble d’indices boursiers. / This Ph.D thesis focuses on modeling, forecasting and hedging financial contagion. After an overview of the theoretical foundations and spread mechanism relating to financial contagion, we introduce modeling based on nonlinear cointegration and non-linear causality models in which the variables and the error term in the correction model error obey at the dynamics of autoregressive regime change process of type TAR and M-TAR to catch the contagion effect. An extension of this model to conditional probabilistic forecasting framework was done through Bayesian belief networks, to enhance the predictive power. Then we show how a financial institution can hedge its portfolio against this risk by new specifications. Therefore, we offer a purely static hedging strategy in a regulatory perspective using generative models Vines-copula, a semi-static hedging strategy based on risk budgeting and dynamic hedging strategy based on mutually exciting jumps diffusion process. These new models are tested empirically on set of market indices.

Submitted thesis deal with estimation safeness of electroplating technologi with reference to occurrence hazardous substances falls on man and environment. To identification diversification was used quantitative risk assessment and chemical exposure index.

学位プログラム名: 京都大学大学院思修館 / 京都大学 / 新制・課程博士 / 博士(総合学術) / 甲第24056号 / 総総博第25号 / 新制||総総||4(附属図書館) / 京都大学大学院総合生存学館総合生存学専攻 / (主査)教授 山敷 庸亮, 教授 寶 馨, 教授 池田 裕一, 佐藤 達彦 / 学位規則第4条第1項該当 / Doctor of Philosophy / Kyoto University / DFAM

Les maladies émergentes à transmission vectorielle sont une préoccupation croissante et particulièrement lorsqu’elles affectent les chevaux, une population spécifiquement à risque vis-à-vis de la propagation de maladies. En effet, les chevaux voyagent fréquemment et, malgré l’impact sanitaire et économique des maladies équines, les règlementations sanitaires et les principes de biosécurité et de traçabilité censés assurer la sécurité des mouvements d'équidés ne sont pas toujours en place. Notre travail propose d'améliorer la surveillance des maladies à transmission vectorielle chez les chevaux en utilisant différentes méthodes pour estimer la probabilité d'émergence d'une maladie. Tout d'abord, nous avons développé un modèle quantitatif et spatio-temporel combinant différentes probabilités pour estimer les risques d'introduction de la peste équine et de l’encéphalose équine. Ces combinaisons permettent d’obtenir une image plus détaillée du risque posé par ces agents pathogènes. Nous avons ensuite évalué des systèmes de surveillance syndromique par deux approches méthodologiques: l'approche classique avec un seuil d'alarme basé sur un multiple de l'erreur standard de prédiction, et l'approche bayésienne basée sur le rapport de vraisemblance. Nous avons travaillé ici principalement sur la détection précoce du virus West Nile en utilisant les symptômes nerveux des chevaux. Les deux approches ont fourni des résultats prometteurs, mais l’approche bayésienne était particulièrement intéressante pour obtenir un résultat quantitatif et pour combiner différentes informations épidémiologiques. Pour finir, l'approche bayésienne a été utilisée pour combiner quantitativement différentes sources d'estimation du risque : surveillance syndromique multivariée, et combinaison de la surveillance syndromique avec les résultats d’analyses de risques. Ces combinaisons ont données des résultats prometteurs. Ce travail, basé sur des estimations de risque, contribue à améliorer la surveillance des maladies à transmission vectorielle chez les chevaux et facilite la prise de décision. Les principales perspectives de ce travail sont d'améliorer la collecte et le partage de données, de mettre en oeuvre une évaluation complète des performances des systèmes de surveillance multivariés, et de favoriser l'adoption de ce genre d’approche par les décideurs en utilisant une interface conviviale et en mettant en place un transfert de connaissance. / Emerging vector-borne diseases are a growing concern, especially for horse populations, which are at particular risk for disease spread. In general, horses travel widely and frequently and, despite the health and economic impacts of equine diseases, effective health regulations and biosecurity systems to ensure safe equine movements are not always in place. The present work proposes to improve the surveillance of vector-borne diseases in horses through the use of different approaches that assess the probability of occurrence of a newly introduced epidemic. First, we developed a spatiotemporal quantitative model which combined various probabilities in order to estimate the risk of introduction of African horse sickness and equine encephalosis. Such combinations of risk provided more a detailed picture of the true risk posed by these pathogens. Second, we assessed syndromic surveillance systems using two approaches: a classical approach with the alarm threshold based on the standard error of prediction, and a Bayesian approach based on a likelihood ratio. We focused particularly on the early detection of West Nile virus using reports of nervous symptoms in horses. Both approaches provided interesting results but Bayes’ rule was especially useful as it provided a quantitative output and was able to combine different epidemiological information. Finally, a Bayesian approach was also used to quantitatively combine various sources of risk estimation in a multivariate syndromic surveillance system, as well as a combination of quantitative risk assessment with syndromic surveillance (applied to West Nile virus and equine encephalosis, respectively). Combining evidence provided promising results. This work, based on risk estimations, strengthens the surveillance of VBDs in horses and can support public health decision making. It also, however, highlights the need to improve data collection and data sharing, to implement full performance assessments of complex surveillance systems, and to use effective communication and training to promote the adoption of these approaches.

Safety study of refuelling station. Diploma thesis, Institute of Metrology and Quality Assurance Testing, Brno University of Technology. This Diploma thesis deal with quantitative risk assessment of exposure. It means for population, animals and environment stocking, transport and manipulation with vairous fuel at refuelling station in particular area and influence of other industrial effects in close area of this refuelling station. There is more specified a Method of Dow´s fire and explosion Index, method of Guidelines for Quantitative Risk Assessment and method FMEA (Failure Mode and Effect Analysis).