No description available.

Risk management is essential for the construction industry to successfully fulfill project objectives. Several studies were conducted in the past decade to support quantitative risk analysis. These studies were based on using some of the commonly used techniques such as risk matrix, decision trees, Monte Carlo, and sensitivity analysis. However, some of these techniques are limited because they either do not support quantitative risk analysis, or are difficult to be utilized due to the required amount of data to support quantitative risk analysis. To address such limitations, a comprehensive framework was developed, based on combining three well-known techniques in reliability engineering, i.e., failure mode and effect analysis, fault trees, and event trees with fuzzy logic. Fuzzy logic and failure mode and effect analysis were first combined to provide an answer to the problem of identifying of critical risk events through the development of a fuzzy expert system software package named Risk Criticality Analyzer. To support quantitative risk analysis in the construction industry, fault tree and event tree were combined, and fuzzy logic is used to solve both of them. Fuzzy arithmetic operations on fuzzy numbers were used to represent logical gates in the fault tree structure, and to conduct event tree analysis. To automate solving both fault trees and event trees, Fuzzy Reliability Analyzer was designed and implemented using Visual Basic.net. Both tools were then validated through case studies. The results indicate that by using the proposed methodology, the risk can be assessed effectively and efficiently. The proposed framework presented in this research provides the contribution of combining fuzzy logic with failure mode and effect analysis, fault trees, and event trees in a comprehensive framework to support risk identification, risk assessment, and risk response. Since the proposed framework is based on using linguistic terms, risk analysts are offered a more convenient and practical framework to conduct risk analysis. The proposed framework was able to address several limitations attributed to the conventional application of failure mode and effect analysis and offered a generic framework that can be adapted to fit any industry or organization. / Construction Engineering and Management

No description available.

The growing application of risk analysis in dam safety, especially for the owners of large numbers of dams (e.g., U.S. Army Corps of Engineers), has motivated the development of a new tool (DAMRAE) for event tree based dam safety risk analysis. Various theoretical challenges were overcome in formulating the computational framework of DAMRAE and several new computational concepts were introduced. The concepts of Connectivity and Pedigree matrices are proposed to quantify the user-drawn event tree structures with proper accounting of interdependencies among the event tree branches. A generic calculation of Common-Cause Adjustment for the non-mutually exclusive failure modes is implemented along with introducing the new concepts of system response probability and consequence freezing. New output presentation formats such as cumulative risk estimate vs. initiating variable plots to analyze the increase of an incremental (annualized) risk estimate as a function of initiating variable are introduced. An additional consideration is given to the non-breach risk estimates in the risk modeling and new output formats such as non-breach F-N and F-$ charts are included as risk analysis outputs. DAMRAE, a Visual Basic.NET based framework, provides a convenient platform to structure the risk assessment of a dam in its existing state and for alternatives or various stages of implementing a risk reduction plan. The second chapter of the dissertation presents the architectural framework of DAMRAE and describes the underlying theoretical and computational logic employed in the software. An example risk assessment is presented in the third chapter to demonstrate the DAMRAE functionalities. In the fourth chapter, the DAMRAE framework is extended into DAMRAE-U to incorporate uncertainty analysis functionality. Various aspects and requirements reviewed for uncertainty analysis in the context of dam safety risk assessment and theoretical challenges overcome to develop the computational framework for DAMRAE-U are described in this chapter. The capabilities of DAMRAE-U are illustrated in the fifth chapter, which contains an example dam safety risk assessment with uncertainty analysis. The dissertation concludes with a summary of DAMRAE features and recommendations for further work in the sixth chapter.

No description available.

Forecasts of short term volcanic activity are generated using an event tree process that is driven by a set of empirical statistical models derived through logistic regression. Each of the logistic models are constructed from a sparse and geographically diverse dataset that was assembled from a collection of historic volcanic unrest episodes. The dataset consists of monitoring measurements (e.g. seismic), source modeling results, and historic eruption information. Incorporating this data into a single set of models provides a simple mechanism for simultaneously accounting for the geophysical changes occurring within the volcano and the historic behavior of analog volcanoes. A bootstrapping analysis of the training dataset allowed for the estimation of robust logistic model coefficients. Probabilities generated from the logistic models increase with positive modeling results, escalating seismicity, and high eruption frequency. The cross validation process produced a series of receiver operating characteristic (ROC) curves with areas ranging between 0.78 - 0.81, which indicate the algorithm has good predictive capabilities. In addition, ROC curves also allowed for the determination of a false positive rate and optimum detection threshold for each stage of the algorithm. The results demonstrate the logistic models are highly transportable and can compete with, and in some cases outperform, non-transportable empirical models trained with site specific information. The incorporation of source modeling results into the event tree’s decision making process has begun the transition of volcano monitoring applications from simple mechanized pattern recognition algorithms to a physical model based forecasting system.

This dissertation research attempts to explore efficient algorithms and engineering methodologies of analyzing the overall reliability and availability of networks integrated with software failures and hardware failures. Node failures, link failures, and software failures are concurrently and dynamically considered in networks with complex topologies. MORIN (MOdeling Reliability for Integrated Networks) method is proposed and discussed as an approach for analyzing reliability of integrated networks. A Simplified Availability Modeling Tool (SAMOT) is developed and introduced to evaluate and analyze the availability of networks consisting of software and hardware component systems with architectural redundancy. In this dissertation, relevant research efforts in analyzing network reliability and availability are reviewed and discussed, experimental data results of proposed MORIN methodology and SAMOT application are provided, and recommendations for future researches in the network reliability study are summarized as well.

This thesis deals with design of a suitable approach for managing the supply of spare parts for machines approaching decommissioning. The appropriate balance between outstanding risks related to equipment downtime and costs of holding spare parts is predicted by proposed systematic algorithm. Determination of key parameters affecting the whole process of spare parts inventory management and their subsequent use as a basis for Event Tree Analysis lead to finding an optimum set-up, which mitigates the overall impact of the planned reduction in spare parts storage levels. The new approach has a number of advantages including versatility of application for many types of machines, as well as a different outlook on a solution for the current issue in spare parts management.

Ouro Preto é uma cidade histórica reconhecida como patrimônio histórico da humanidade pela UNESCO, que tem um passado de intensa exploração mineral e construções sem nenhum planejamento e critério desde 1680. Recentemente, várias ocorrências de escorregamento, quedas e outros movimentos gravitacionais de massa têm ocorrido na área. A ocorrência dos movimentos gravitacionais de massa é atribuída às chuvas associadas aos fatores predisponentes e modificadores que existem na área. Observa-se que o grande problema não é a magnitude desses processos, mas sim a freqüência com que eles ocorrem. Neste contexto, apresenta-se neste trabalho a previsão de movimentos gravitacionais de massa na Serra de Ouro Preto a partir de árvore de eventos. A avaliação probabilística é realizada a partir de árvore de eventos, para que valores quantitativos sejam atribuídos a cada atributo. Por meio desta análise, é possível se obter uma previsão quantitativa dos possíveis hazards e problemas que podem ser esperados na região. Cada tipo de movimento gravitacional de massa é composto por uma seqüência condicionada de atributos que deve ser considerada, e para cada um deles, a probabilidade de ocorrência foi estabelecida considerando os aspectos probabilísticos. A probabilidade de cada atributo foi determinada pela freqüência relativa do atributo no cenário (análise unidimensional) e a sua intensidade (análise bidimensional). Conclui-se que os principais processos de movimentos gravitacionais de massa que ocorrem na área são classificados como escorregamentos translacionais (em rocha e em material inconsolidado), rolamentos (em rocha, detritos e em blocos de rocha), corridas, quedas (em rocha, blocos de rocha e em material inconsolidado), escoamentos (em detritos e em material inconsolidado), complexo (em rocha e em material inconsolidado) os quais apresentam-se ativos (todos sem nenhuma exceção). Quanto aos valores de probabilidades calculados para os processos de movimentos gravitacionais de massa, obteve-se valores de 1 a 17 porcento, resultando num período de retorno de 50 a 5 anos. Estes valores permitem caracterizar a área como uma zona perigosa e potencialmente perigosa. / Ouro Preto is a historical city that enjoys the World Heritage Landmark Status as granted by UNESCO, and has a history of heavy mining and rampant unstructured housing dating back to 1680. Recently there have been many occurrences of landslides, rock fall and other landslide hazards. The effects of rainfall events associated with predisposing and modifying factors that exist in the area are attributed to the occurrence of landslides. It should be noted that the biggest problem is not the magnitude of these hazards, but the frequency with they occur. Thus, the assessment of landslide processes in Ouro Preto is presented through event tree form. The probabilistic analysis is performed in an event tree form in order to give quantitative values for every attribute. Such analysis allows a quantitative prediction of the possible hazards and problems that can be expected in the region. Every type of landslide process has a conditional sequence of attributes that must be taken into account and for every kind of attribute the probability of occurrence is established through probabilistic aspects. The probability of every attribute is identified by its relative frequency in the scenario (one-dimensional analysis) and the intensity (two-dimensional analysis). It was possible to conclude that the main landslide processes that occur in the area are classified as translational slides, bouncing or rolling, quickly flows, falls, flows and complex and all the processes are currently active. Concerning the probability values that were calculated for the landslide processes, a range from 1 to 17 percent, they resulted in a return period from 50 to 5 years. These values allow characterizing the area as a dangerous to a potentially dangerous zone.

Ouro Preto é uma cidade histórica reconhecida como patrimônio histórico da humanidade pela UNESCO, que tem um passado de intensa exploração mineral e construções sem nenhum planejamento e critério desde 1680. Recentemente, várias ocorrências de escorregamento, quedas e outros movimentos gravitacionais de massa têm ocorrido na área. A ocorrência dos movimentos gravitacionais de massa é atribuída às chuvas associadas aos fatores predisponentes e modificadores que existem na área. Observa-se que o grande problema não é a magnitude desses processos, mas sim a freqüência com que eles ocorrem. Neste contexto, apresenta-se neste trabalho a previsão de movimentos gravitacionais de massa na Serra de Ouro Preto a partir de árvore de eventos. A avaliação probabilística é realizada a partir de árvore de eventos, para que valores quantitativos sejam atribuídos a cada atributo. Por meio desta análise, é possível se obter uma previsão quantitativa dos possíveis hazards e problemas que podem ser esperados na região. Cada tipo de movimento gravitacional de massa é composto por uma seqüência condicionada de atributos que deve ser considerada, e para cada um deles, a probabilidade de ocorrência foi estabelecida considerando os aspectos probabilísticos. A probabilidade de cada atributo foi determinada pela freqüência relativa do atributo no cenário (análise unidimensional) e a sua intensidade (análise bidimensional). Conclui-se que os principais processos de movimentos gravitacionais de massa que ocorrem na área são classificados como escorregamentos translacionais (em rocha e em material inconsolidado), rolamentos (em rocha, detritos e em blocos de rocha), corridas, quedas (em rocha, blocos de rocha e em material inconsolidado), escoamentos (em detritos e em material inconsolidado), complexo (em rocha e em material inconsolidado) os quais apresentam-se ativos (todos sem nenhuma exceção). Quanto aos valores de probabilidades calculados para os processos de movimentos gravitacionais de massa, obteve-se valores de 1 a 17 porcento, resultando num período de retorno de 50 a 5 anos. Estes valores permitem caracterizar a área como uma zona perigosa e potencialmente perigosa. / Ouro Preto is a historical city that enjoys the World Heritage Landmark Status as granted by UNESCO, and has a history of heavy mining and rampant unstructured housing dating back to 1680. Recently there have been many occurrences of landslides, rock fall and other landslide hazards. The effects of rainfall events associated with predisposing and modifying factors that exist in the area are attributed to the occurrence of landslides. It should be noted that the biggest problem is not the magnitude of these hazards, but the frequency with they occur. Thus, the assessment of landslide processes in Ouro Preto is presented through event tree form. The probabilistic analysis is performed in an event tree form in order to give quantitative values for every attribute. Such analysis allows a quantitative prediction of the possible hazards and problems that can be expected in the region. Every type of landslide process has a conditional sequence of attributes that must be taken into account and for every kind of attribute the probability of occurrence is established through probabilistic aspects. The probability of every attribute is identified by its relative frequency in the scenario (one-dimensional analysis) and the intensity (two-dimensional analysis). It was possible to conclude that the main landslide processes that occur in the area are classified as translational slides, bouncing or rolling, quickly flows, falls, flows and complex and all the processes are currently active. Concerning the probability values that were calculated for the landslide processes, a range from 1 to 17 percent, they resulted in a return period from 50 to 5 years. These values allow characterizing the area as a dangerous to a potentially dangerous zone.