Bruce R. Ellingwood

Performance Indicators for Structural Systems and Infrastructure Networks

AbstractEstablishing consistent criteria for assessing the performance of structural systems and infrastructure networks is a critical component of communities’ efforts to optimize investment decisions for the upkeep and renewal of the built environment. Although member-level performance and reliability assessment procedures are currently well-established, it is widely recognized that a member-oriented approach does not necessarily lead to an efficient utilization of limited resources when making decisions related to the management of existing deteriorating structures or lifeline systems, especially those that may be exposed to extreme events. For this reason, researchers have renewed their interests in developing system-level assessment methods as a basis to modern structural and infrastructure performance evaluation and design processes. Specifically, system-level performance metrics and characteristics such as reliability, redundancy, robustness, resilience, and risk continue to be refined. The objecti...

A risk de-aggregation framework that relates community resilience goals to building performance objectives

Abstract Resilience is often regarded as an attribute of communities rather than of individual buildings, bridges, and other civil infrastructure facilities. Previous research to support development of resilient infrastructure has considered, for the most part, actions and policies to achieve resilience objectives at the community level. While it is clear that a community cannot be resilient without resilient individual facilities, few attempts have been made to relate the performance criteria for individual facilities to community resilience goals in a quantitative manner. This paper presents a method for relating risk-informed performance criteria for individual buildings exposed to extreme hazards to broader community resilience objectives and illustrates the application of the method to two residential building inventories. The paper demonstrates the feasibility of de-aggregating community resilience goals to obtain design performance objectives for individual facilities and thereby relating community goals to requirements in codes and standards that govern design of buildings and other structures.

The Centerville Virtual Community: a fully integrated decision model of interacting physical and social infrastructure systems

Abstract Enhancing community resilience in the future will require new interdisciplinary systems-based approaches that depend on many disciplines, including engineering, social and economic, and information sciences. The National Institute of Standards and Technology awarded the Center for Risk-Based Community Resilience Planning to Colorado State University and nine other universities in 2015, with the overarching goal of establishing the measurement science for community resilience assessment. The Centerville Virtual Community Testbed is aimed at enabling fundamental resilience assessment algorithms to be initiated, developed, and coded in a preliminary form, and tested before the refined measurement methods and supporting data classifications and databases necessary for a more complete assessment have fully matured. This paper introduces the Centerville Testbed, defining the physical infrastructure within the community, natural hazards to which it is exposed, and the population demographics necessary to assess potential post-disaster impacts on the population, local economy, and public services that are described in detail in the companion papers of this Special Issue.

Time-dependent reliability of ageing structures: an approximate approach

Abstract Concrete structures may deteriorate over time due to aggressive service environments, leading to a reduction in their strengths, stiffnesses and reliabilities. In general, the assessment of time-dependent reliability of ageing structures must consider uncertainties in structural deterioration as well as non-stationarities in the structural load processes. This paper develops an approximate method for assessing the impact of structural deterioration and non-stationary live loads on structures, which requires only low-dimensional integration and reduces the cost of assessing time-dependent reliability over a service life extending to 50 years significantly. This approximate method is demonstrated through several examples. The importance of non-stationarities in the resistance and load processes on time-dependent reliability is illustrated and the accuracy of the method is confirmed in several cases utilising Monte Carlo simulation.

Probability Models for Annual Extreme Water-Equivalent Ground Snow

Abstract A statistical analysis of annual extreme water-equivalents of ground snow (reported as inches of water) measured up through the winter of 1979–80 at 76 weather stations in the northeast quadrant of the United States is presented. The analysis suggests that probability distributions with longer upper tails than the Type I distribution of extreme values are preferable for describing the annual extremes at a majority of sites. Sampling errors and the selection of water-equivalents for planning and design purposes also are described.

State of the research in community resilience: progress and challenges

Abstract Community resilience has been addressed across multiple disciplines including environmental sciences, engineering, sociology, psychology, and economics. Interest in community resilience gained momentum following several key natural and human-caused hazards in the United States and worldwide. To date, a comprehensive community resilience model that encompasses the performance of all the physical and socio-economic components from immediate impact through the recovery phase of a natural disaster has not been available. This paper summarizes a literature review of previous community resilience studies with a focus on natural hazards, which includes primarily models of individual infrastructure systems, their interdependencies, and community economic and social systems. A series of national and international initiatives aimed at community resilience are also summarized in this study. This paper suggests extensions of existing modeling methodologies aimed at developing an improved, integrated understanding of resilience that can be used by policy-makers in preparation for future events.

Reliability-based optimal load factors for seismic design of buildings

Abstract—Optimal load factors (dead, live and seismic) used for the design of buildings may be different, depending of the seismic ground motion characteristics to which they are subjected, which are closely related to the type of soil conditions where the structures are located. The influence of the type of soil on those load factors, is analyzed in the present study. A methodology that is useful for establishing optimal load factors that minimize the cost over the life cycle of the structure is employed; and as a restriction, it is established that the probability of structural failure must be less than or equal to a prescribed value. The life-cycle cost model used here includes different types of costs. The optimization methodology is applied to two groups of reinforced concrete buildings. One set (consisting on 4-, 7-, and 10-story buildings) is located on firm ground (with a dominant period Ts  0.5 s) and the other (consisting on 6-, 12-, and 16-story buildings) on soft soil (Ts  1.5 s) of Mexico City. Each group of buildings is designed using different combinations of load factors. The statistics of the maximums interstory drifts (associated with the structural capacity) are found by means of incremental dynamic analyses. The buildings located on firm zone are analyzed under the action of 10 strong seismic records, and those on soft zone, under 13 strong ground motions. All the motions correspond to seismic subduction events with magnitudes M  6.9. Then, the structural damage and the expected total costs, corresponding to each group of buildings, are estimated. It is concluded that the optimal load factors combination is different for the design of buildings located on firm ground than that for buildings located on soft soil.

The Impact of Climate Change on Resilience of Communities Vulnerable to Riverine Flooding

Riverine flooding due to intense precipitation or snowmelt is one of the most devastating natural hazards in the United States in terms of annual damages and economic losses to the built environment and social impacts on communities. Flood inundation mapping, where the likely depths of extreme floods are placed on a map of the community, is important for evaluating flood risks and for enhancing community resilience. However, the Flood Insurance Rate Maps developed by the Federal Emergency Management Agency are not adequate for the evolving needs for community resilience assessment and decision-making over the next century, during which climate change effects are likely to be significant. In this study, we develop a flood hazard modeling framework to support community resilience assessment. This framework couples a hydrological model, which simulates the hydrological processes in a community at a coarser resolution using measured and/or remote sensed precipitation, with a hydraulic analysis module, which computes localized flood depths, velocities and inundated areas at a finer spatial resolution. The Wolf River Basin in Shelby County, Tennessee, which includes the city of Memphis, is used as a testbed to calibrate and validate this coupled model using precipitation and streamflow data obtained from gauge stations operated by the US Geological Survey and to illustrate the potential impacts of climate change in the 21st Century on civil infrastructure, revealing that such impacts are non-negligible but are manageable by proper engineering.

Developing measurement science for community resilience assessment

Community resilience depends on the performance of the built environment and on supporting social, economic and public institutions which are essential for the recovery of a community following a disaster. A community’s social needs and objectives (including post-disaster recovery) are not reflected in the codes, standards and other regulatory documents that traditionally have been applied to the design and construction of individual facilities. A new approach is required, one that reflects the complex interdependencies among the physical, social, and economic systems on which a resilient and vibrant community depends. Thus, modeling the resilience of communities and cities to natural hazards depends on many disciplines, including engineering, social sciences, and information sciences. Resilience assessment has become an imperative in many countries, including the United States, Europe and the Asia-Pacific Rim. The Center for Risk-Based Community Resilience Planning, headquartered at Colorado State University in Fort Collins, Colorado and involving 10 universities and nearly 100 investigators, was established by the National Institute of Standards and Technology (NIST) in 2015. The Center’s overarching goal is to establish the measurement science needed to study and understand the factors that make a community resilient, to assess the likely impact of natural (and eventually other) hazards on communities, and to develop risk-informed decision strategies that optimize both planning for and recovery from disasters. To accomplish this goal, the Center is engaged in three major research thrusts aimed at (1) developing the Interdependent Networked Community Resilience modeling environment (IN-CORE) to assess alternative community resilience strategies quantitatively; (2) instituting a standardized data ontology, robust architecture and management tools supporting the modeling environment; and (3) performing a comprehensive set of testbeds and hindcasts to validate this advanced modeling environment. Several community resilience testbeds have been initiated during the Center’s first year. These testbeds have been designed to: (1) allow Center research teams to initiate, test, and modify essential community resilience assessment models and algorithms before the IN-CORE platform becomes fully operational; (2) stress these assessment models in a controlled manner; (3) examine varying degrees of dependency between physical, social, and economic infrastructure systems; and (4) facilitate the interdisciplinary collaborations and approaches to community resilience assessment that will be essential for the Center to achieve its ultimate goal. This special issue of Sustainable and Resilient Infrastructure is devoted to the first of these testbeds – the Centerville Virtual Community. Centerville is envisioned as a community in the Central United States that is susceptible to earthquake and tornado hazards. In most respects, it is a typical, middle-class, community of moderate size, with a median household income that is close to the national average in the United States and a diversified economy that includes commercial/retail, professional services, education/health care, industrial and government sectors. The physical infrastructure includes a variety of residential, commercial, and industrial buildings, bridges and transportation facilities, and utility networks. The physical, social, and economic systems, and

Reliabilities of steel structural systems designed by inelastic analysis

Severalnationalsteeldesignstandards allow,inprinciple, theuseofinelastic system analysis to check the integrity of a steel structural system. However, system reliability considerations have yet to be implemented in any rational way in such design-byinelastic analysis methods. This paper considers a representative steel moment frame subjected to combined gravity and wind loads. The frame is designed using secondorder inelastic analysis with a set of postulated system resistance factors. The probabilities of occurrence of strength and serviceability limit states are evaluated. The effects on these limit state probabilities of system resistance factor and wind-to-gravity load ratio are examined.