ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 

About: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering is an academic journal published by American Society of Civil Engineers. The journal publishes majorly in the area(s): Reliability (statistics) & Probabilistic logic. It has an ISSN identifier of 2376-7642. Over the lifetime, 457 publications have been published receiving 4264 citations. The journal is also known as: Journal of risk and uncertainty in engineering systems: Part A : Civil engineering & American society of Civil Engineers and American Society of Mechanical Engineers journal of risk and uncertainty in engineering systems: Part A : Civil engineering.

Rare Event Estimation Using Polynomial-Chaos Kriging

Abstract: Structural reliability analysis aims at computing the probability of failure of systems whose performance may be assessed by using complex computational models (e.g., expensive-to-run finite-element models). A direct use of Monte Carlo simulation is not feasible in practice, unless a surrogate model (such as kriging, also known as Gaussian process modeling) is used. Such metamodels are often used in conjunction with adaptive experimental designs (i.e., design enrichment strategies), which allows one to iteratively increase the accuracy of the surrogate for the estimation of the failure probability while keeping low the overall number of runs of the costly original model. This paper develops a new structural reliability method based on the recently developed polynomial-chaos kriging (PC-kriging) approach coupled with an active learning algorithm known as adaptive kriging Monte Carlo simulation (AK-MCS). The problem is formulated in such a way that the computation of both small probabilities of fail...

Practical Resilience Metrics for Planning, Design, and Decision Making

Abstract: Natural disasters in 2011 alone resulted in $366 billion (2011 US$) in direct damages and 29,782 fatalities worldwide. Storms and floods accounted for up to 70% of the 302 natural disasters worldwide, with earthquakes producing the greatest number of fatalities. Managing these risks rationally requires an appropriate definition of resilience and associated metrics. This paper provides a resilience definition that meets a set of requirements with clear relationships to reliability and risk as key relevant metrics. The resilience definition proposed is of the intension type, which is of the highest order. Resilience metrics are reviewed, and simplified ones are proposed to meet logically consistent requirements drawn from measure theory. Such metrics provide a sound basis for the development of effective decision-making tools for multihazard environments. The paper also examines recovery, with its classifications based on level, spatial, and temporal considerations. Three case studies are developed ...

Scale of Fluctuation for Spatially Varying Soils: Estimation Methods and Values

Abstract: Spatial variability is one of the major sources of uncertainty in geotechnical applications. This variability is characterized customarily by the scale of fluctuation. Scale of fluctuation ...

Engineering Decisions under Risk Averseness

Abstract: Engineering decisions are invariably made under substantial uncertainty about current and future system cost and response, including cost and response associated with low-probability, high-consequence events. A risk-neutral decision maker would rely on expected values when comparing designs, while a risk-averse decision maker might adopt nonlinear utility functions or failure probability criteria. The paper shows that these models for making decisions are related to a framework of risk measures that includes many possibilities. The authors describe how risk measures provide an expanded set of models for handling risk-averse decision makers. General recommendations for selecting risk measures lead to decision models for risk-averse decision making that comprehensively represent risks in engineering systems, avoid paradoxes, and accrue substantial benefits in subsequent risk, reliability, and cost optimization. The paper provides an overview of the framework of decision making based on risk measures.

Climate Impact Risks and Climate Adaptation Engineering for Built Infrastructure

Abstract: A changing climate may increase the frequency or intensity of natural hazards, resulting in increased infrastructure damage. The paper will describe how risk-based approaches are well suited to optimising climate adaptation strategies related to the construction, design, operation, and maintenance of built infrastructure. Climate adaptation engineering involves estimating the risks, costs, and benefits of climate adaptation strategies and assessing at what point in time climate adaptation becomes economically viable. Stochastic methods are used to model infrastructure performance, risk reduction, and effectiveness of adaptation strategies, exposure, and costs. These concepts will be illustrated with recent research on risk-based life-cycle assessments of climate adaptation strategies for Australian housing subject to extreme wind events. This will pave the way for more efficient and resilient infrastructure, and help future proof new and existing infrastructure to a changing climate.