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Bridge scour is the loss of soil by erosion because of water flowing around bridge supports. Scour has been the number one cause of bridge failure in the United States with an average annual rate of 22 bridges collapsing or being closed owing to severe deformation. This paper addresses three topics related to bridge scour. First, a set of databases was used to quantify the statistical parameters associated with the scatter between the predicted and measured pier scour depth, as well as the probability that a deterministically predicted pier scour depth will be exceeded. These databases also were used to provide the bias factors in current predictions. Secondly, these statistical parameters were used to develop a reliability-based load and resistance factor design for shallow and deep foundations subjected to scour. The goal was to provide a design procedure where the reliability of the foundation is the same with or without scour. Reliability only addresses the probability of success and, therefore, of failure. Finally, the discussion was broadened by using the concept of risk defined as the probability of failure times the value of the consequences. In this third part, the risk associated with bridge scour was quantified and compared to risks associated with other engineering structures. Target values of acceptable risk were recommended as part of the conclusions. [ABSTRACT FROM AUTHOR]

Characterization of critical water distribution system (WDS) contamination scenarios-defined by a set of attributes, a probability of occurrence, and a specific level of consequences-is a prerequisite for preparation of reliable and cost-effective mitigation, preparedness, and emergency response plans. This study develops Monte Carlo and risk-based optimization schemes to evaluate contamination risk of WDSs for generation of this important class of scenarios, which are representative of the most vulnerable aspects of the system. Defining attributes of contamination scenarios are identified as contaminant type and amount, contamination location, start time, duration, and time of year scenario occurs. Well-documented waterborne outbreaks reported in developed nations are analyzed to empirically estimate statistical characteristics of defining attributes in accidental events. Monte Carlo simulation is conducted to determine the probability distribution of public-health consequences, aggregate conditional risk, and significance of different scenario attributes. A multiobjective optimization methodology is proposed to capture the attributes of critical accidental contamination scenarios. The principal risk components of likelihood and health consequences are treated as optimization objectives and are maximized simultaneously to identify an ensemble of nondominated critical scenarios. The multiobjective approach provides insight into system risk and potential mitigation options not available under maximum-risk or maximum-consequences analyses. Performance and applicability of developed models is demonstrated on the WDS of a virtual midsize city that possesses characteristics of complex real-world distribution networks. [ABSTRACT FROM AUTHOR]

This study introduces a new probabilistic project control concept to assure an acceptable forecast of final project performance, in terms of not exceeding planned budget and schedule risk levels. This concept consists in the implementation of performance control limit curves for both actual cost and elapsed time, obtained with a probabilistic approach and a graphical representation referred to as Stochastic S curves (SS curves). In order to facilitate the project control process, control limit curves can be used to display and evaluate actual project performance status without the need of actualizing at completion performance forecasts. Three different approaches (quality, benchmarking, and incremental variance) are proposed in this paper for obtaining the project performance control limit curves. In order to find the control limit curve definition with more conservative acceptable performance variations, these approaches are tested in an example project. A further managerial advantage is found in the recommended approach, as it allows monitoring the use of both cost and scheduling contingencies, along the project execution. [ABSTRACT FROM AUTHOR]

Over 10,000 failures have occurred in US oil and gas pipelines in the past 15 years, highlighting the significance of safety measures for such facilities. Various models have been proposed by researchers to predict different failure parameters. Despite such efforts, no comprehensive review has yet been conducted in this domain. The objective of this study is to provide a detailed review of the methodologies proposed to predict failure parameters for oil and gas pipelines. Such a review gathers, organizes, classifies, and analyzes previous contributions in this domain and highlights the gaps associated with different failure prediction models. In addition, the current code-based methodologies for predicting the failure of oil and gas pipelines and their corresponding limitations are discussed. As such, this study provides pipeline operators and researchers with a comprehensive overview of the research and practices in oil and gas pipeline failure and safety. In conclusion, several avenues for future research are discussed. In particular, a maintenance planning procedure directed by pipeline availability analysis is proposed to address the existing gaps and limitations. [ABSTRACT FROM AUTHOR]