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Tornadoes pose a significant threat to residential communities, causing enormous physical damage and losses to their social fabric. The dominant type of single-family residential buildings in the USA is light-frame wood construction, which is especially susceptible to tornado effects. Previous studies considering resilience of light-frame wood buildings have focused primarily on assessing damage, developing damage functions, and exploring different repair methods. Studies related to sustainability have focused mainly on environmental impacts or carbon usage. Practically all of these studies have been geared to assessment of individual buildings. In this study, we couple resilience and sustainability to evaluate their tradeoffs or alignments at the community level from a life-cycle stance. The life-cycle cost and carbon footprint are reflected in the construction and repair of damages due to the tornado hazard, as well as regular repair and maintenance that occurs during the life of the residence. Uncertainties in the randomness in tornado occurrence, size of the tornado footprint, and variation in wind speed intensities within the tornado footprint, and capacities of the building structure and envelope play a significant role in building performance and are considered. We explore a number of repair strategies that might be adopted at the community level in decision-making and policy formulation for homeowners, home builders and community planners. These strategies provide a framework for integrating minimum cost and carbon footprint objectives in risk-informed decision-making, a topic that appears to be lacking in the literature.

Bridges are an important type of transportation infrastructures. Once more than one bridge in a transportation network is extensively or completely damaged in a severe earthquake, the traffic capac...

Surface transportation systems are an essential part of urban transportation infrastructure and are susceptible to damage from earthquakes. This damage, along with the lack of prior warning of eart...

For households of all income levels, and especially for those that are food insecure, food access can be threatened by natural hazards. Extreme natural hazards can disrupt critical infrastructure s...

Natural disasters may have catastrophic and long‐lasting impacts on communities' physical, economic, and social infrastructure. Slow recovery of educational services following such events is likely to cause traumatic stress in children, lead families to out‐migrate, and affect the community's overall social stability. Methods for quantifying and assessing the restoration process of educational systems and their dependencies on other supporting infrastructure have not received adequate attention. This study introduces, for the first time, a new framework to evaluate the functionality, recovery, and resilience of a school system following severe earthquake events. The framework considers both the quantity and quality of education services provided, school enrollment, and staff employment, as well as the interaction between various agents such as staff, students, parents, administration, and community. A virtual testbed community, Centerville, is utilized to highlight the application of this framework. The impact of school reopening policies on the number of students enrolled as well as the potential for homeschooling is also considered. The availability of various enrollment alternatives for students, backup classroom space and functioning utility systems, and facilitation of staff and supplies transfer between schools substantially increase the resilience of the education service., Key Points A new framework is devised to estimate the resilience and functionality of K‐12 schools after earthquakesThe framework considers the role played by the society on maintaining the schools' functionalityA Markov chain stochastic model, coupled with dynamic optimization, is used to model the near‐optimal school recovery trajectory of the schools

Light-framed residential wood buildings constitute the majority of residential construction in the U.S. These buildings seldom are engineered for specific hazards. As a result, they may be inadequate to ensure life safety, let alone continued functionality during and after a severe natural hazard. The aims of this study are twofold: to assess the performance of light-frame wood residential buildings under tornado hazards, and to link performance of individual building components to building system performance so that the effect of implementing improved construction techniques can be quantified. These goals were realized through the development of detailed finite element models to capture individual building component behavior and building system performance under tornado wind pressure loading. Based on the data acquired from the finite element models, tornado wind fragilities (damage state probabilities) were developed for several building archetypes. First, typical construction quality was considered to establish a frame of reference; subsequently various improved construction techniques were considered in an effort to meet community resilience performance targets provided from concurrent research. The study shows that, while current construction practices fail to meet risk-informed building performance criteria needed to achieve community resilience goals, these goals can be achieved by modest improvements to existing construction techniques.

The paradigm of performance-based engineering (PBE) provides a framework for engineers and planners to achieve desired levels of performance and functionality of building clusters and civil infrastructure systems that are essential for community resilience and well-being. While it is recognized that resilience of a community must be supported by individual buildings and engineered facilities, the relation between community resilience goals and minimum performance criteria of individual structures enabling such goals through engineering practices does not yet exist. In this study, we first propose a path forward to establish this relation in a quantitative manner. We then illustrate the feasibility of the proposed framework by de-aggregating the resilience goals of a community residential building cluster through an inverse multi-objective optimization formulation to obtain the minimum performance objectives for residential buildings, for tornado hazards. Once the minimum building performance criteria are determined, they can be utilized as the target building performance for new constructions, pre-event strengthening or post-event reconstruction. The overarching aim of this framework is to relate engineering design and retrofit practices to socioeconomic expectations of a community as a whole, and to provide a vehicle for risk-informed resilience-based decision-making under natural hazard events.

A reliability-based development of load factors for the combination of seismic and gravity loads is presented. The procedure aims at minimizing the total expected life-cycle cost of buildings, having as a constraint a maximum value of the mean annual failure rate. The loads considered are dead, live and earthquake loads. The methodology is applied to a large inventory of reinforced concrete frames and steel frames buildings located at a soft soil region of Mexico City. Artificial Neural Networks are used to efficiently obtain the designs and the reliabilities of the buildings in the inventory. For the range of load combinations studied, the optimal load factors were found to be insensitive to the value of life, but sensitive to the fundamental vibration period of the structures.

Flood risk is increasing in urban communities due to climate change and socioeconomic development. Socioeconomic development is a major cause of urban expansion in flood-prone regions, as it places more physical, economic, and social infrastructure at risk. Moreover, in light of the 2030 Agenda for Sustainable Development by the United Nations, it has become an international imperative to move toward sustainable cities. Current approaches to quantify this risk use scenario-based methods involving arbitrary projections of city growth. These methods seldom incorporate geographical, social, and economic factors associated with urbanization and cannot mimic city growth under various urban development plans. In this paper, we introduce a framework for understanding the interactions between urbanization and flood risk as an essential ingredient for flood risk management. This framework integrates an urban growth model with a hazard model to explore flood risk under various urban development scenarios. We then investigate the effectiveness of coupling nonstructural flood mitigation measures—in terms of urban planning policies and socioeconomic incentives—with urban growth processes to achieve sustainable and resilient communities. Using this framework, we can not only simulate urban expansion dynamics through time and its effect on flood risk but also model the growth of a region under various urban planning policies and assess the effectiveness of these measures in reducing flood risk. Our analysis reveals that while current urban development plans may put more people and assets at flood risk, the nonstructural strategies considered in this study mitigated the consequences of floods. Such a framework could be used to assist city planners and stakeholders in examining tradeoffs between costs and benefits of future land development in achieving sustainable and resilient cities.

Approximately 10% of the world's population lives and works in low-lying coastal regions that are less than 10 m above sea level. This percentage is likely to increase during the remainder of the 21st century due to population growth and economic development. This growth brings the potential for increasing damage and economic losses due to tropical cyclones (hurricanes in North America) accompanied by storm surge and sea-level rise (SLR) in an era of climate change. This study reviews and critically appraises the potential impact of the aforementioned multi-hazards on a typical coastal seaport community in the Gulf Coast of the United States. A new model for quantifying the functionality of seaports subject to these multi-hazards is implemented in a fault tree analysis. An analysis to enable the study of the impact of hurricanes, storm surge, and SLR on port facilities is validated using data from Hurricane Katrina. A case study of the Port of Mobile, AL reveals that if a Katrina-like hurricane were to occur late in the 21st Century, damages to the Port of Mobile would increase by a factor of nearly 7 under an RCP 8.5 scenario when compared to the damages caused by Hurricane Katrina alone.

Probabilistic damage evaluation and loss estimation of spatially distributed infrastructure systems (e.g. an electric power system or a building portfolio) under a scenario tropical cyclone must consider the spatial correlation of cyclone wind speeds to estimate their impact on the built environment statistically. Previous studies have seldom considered the impact of this spatial correlation on damage assessments of distributed civil infrastructure. In this paper, a stochastic field model is developed to capture the uncertainty of cyclone wind speeds and their spatial correlation for the North Atlantic region. A series of recorded wind speed fields of historical cyclone events are examined. The bias values between the recorded wind speeds and computed wind speeds based on a widely used cyclonic wind field model are obtained. The statistics of the wind field bias are estimated using geostatistical tools. The effect of wind speed uncertainty and spatial correlation on performance assessment of distributed infrastructure systems is illustrated using an electric power system, where the metrics of performance are damage ratio, outage ratio and outage cost.

This study assesses the life-cycle probability of survival of a deteriorating reinforced concrete girder bridge subjected to earthquake and pier scour. Adopting a component level approach, the framework of reliability assessment of bridge is established for its service life. The framework is established by the following three steps: 1) establish the probabilistic models of natural hazards; 2) capture the responses of bridge subjected to multiple hazards using SAP2000; 3) utilize methods of time-dependent reliability to assess the probability of survival of the bridge during its service life. The result shows that comparing to the pier scour, deterioration affects the seismic fragility of the bridge more significantly; however, pier scour could lengthen the natural period of bridge, and reduce the seismic response of the bridge, when the scour depth is under a specific level. It would underestimate the effects of multi-hazard to consider the hazards individually, when the correlation of structural effects induced by multi-hazards is negative, and the effects could be overestimated when the correlation is positive. This study reveals the two types of the correlations for the seismic fragility analysis of the reinforced concrete bridge, which should be noticed when design and operate a bridge subjected to multi-hazard.

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...

The design of steel frames by advanced analysis (second-order inelastic analysis with imperfections) of overall system behaviour is permitted in the American steel specification AISC360-10 and the Australian Standard AS4100. In both specifications, the strength of a structural frame can be determined by a rigorous system nonlinear analysis in lieu of checking member resistances to the specific provisions of the Specification, provided that the limit states covered by the Specification equations are detected by the inelastic analysis, and a comparable or higher level of structural reliability is achieved by the inelastic analysis than by member-based design. This system-based, design-by-advanced analysis approach is termed “Direct Design Method” (DDM). In DDM, a system resistance factor is applied to the frame strength. The system factor in AISC360-10 was adopted without considering its impact on frame reliability. This paper describes the framework for developing reliability-based system resistance factors suitable for use with DDM. A simple frame is used to demonstrate the procedures. Appropriate system resistance factors for various load cases and design recommendations are presented in a companion paper [1] based on the system reliability analyses of a series of steel frames.

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 ...

Light-frame wood building construction dominates the single-family residential home market in the United States. Such buildings are susceptible to damage from extreme winds due to hurricanes in coastal areas and tornados in the Midwest. The consequences of extreme winds on the built environment and on social and economic institutions within the community can be severe and are likely to increase in the coming decades as a result of increases in urbanization and economic development and the potential impacts of changing climate in hazard prone areas. Current building practices provide minimum standards for occupant safety and health, including structural integrity, water and sanitation, lighting, ventilation, means of egress and fire protection. However, they generally do not consider building resilience, which includes robustness and an ability to recover following extreme natural hazard events. Nor do they address sustainability, the notion that building design, construction and rehabilitation should not adversely impact the environment. In this paper, we establish a generalized cost and carbon footprint life-cycle analysis methodology for examining the benefits of different building practices for residential light-frame wood construction subjected to tornado hazards. A multi-objective approach is used to reveal tradeoffs between resilient and sustainable practices for typical residential construction. We show that when the life cycle of a typical residence is considered, a balance between resilience, sustainability and cost might be achieved in design and rehabilitation of residential building construction for tornado hazards.

The catastrophic social, economic, and political impact from extreme natural hazards in recent years, e.g. Hurricane Katrina (2005), the Christchurch Earthquake (2011), and the Great East Japan Earthquake and Tsunami (2011), have engendered questions from public officials, engineers and planners as to how a community’s damaged building portfolio might be best reconstructed to enhance its performance in future hazards. The concept of building back better reflects a reconstruction approach aimed at enabling the community to achieve better performance in future hazard events. Building portfolio life-cycle analysis, developed in a concurrent study, can quantify the impact of specific reconstruction policies and decisions on the building portfolio within a community. This approach, coupled with community-dependent resilience goals aimed at limiting functionality loss and ensuring quick recovery, is utilized in this study to suggest optimal policies for post-disaster reconstruction and to guide cost-effective public decisions aimed at ensuring community resilience. The feasibility of this concept is explored using reconstruction of a mid-size community following a severe earthquake as an example in which key features that may affect optimal reconstruction decisions by community planners are identified.

The absorptive and restorative abilities of a community are two key elements of community resilience following disasters. The recovery of communities relies on an efficient restoration planning of damaged critical infrastructure systems, household units, and impaired supporting social and economic functions. These interdependent systems form a dynamic system of systems that changes continuously during restoration. Therefore, an effective and practical recovery planning process for a community can be modeled as a sequential dynamic optimization problem under uncertainty. This paper seeks to enhance our understanding of dynamic optimization concepts and their role in formulating post-disaster, community-level recovery strategies. Various methods of classic dynamic programming and reinforcement learning are examined and applied. Simulation-based approximate dynamic programming techniques are introduced to overcome the curse of dimensionality, which is characteristic of large-scale and multi-state systems of systems. The paper aims not only to study the unexplored topic of dynamic optimization in community resilience, but also to be a practical reference for policymakers, practitioners, engineers, and operations analysts to harness the power of dynamic optimization toward assessing and achieving community resilience.

ASCE 7 is moving toward adopting load requirements that are consistent with risk-informed design goals characteristic of performance-based engineering (PBE). ASCE 7-10 provided wind maps that correspond to return periods of 300, 700, and 1,700 years for Risk Categories I, II, and combined III/IV, respectively. The risk targets for Risk Categories III and IV buildings and other structures (designated as essential facilities) are different in PBE. The reliability analyses reported in this paper were conducted using updated wind load data to (1) confirm that the return periods already in ASCE 7-10 were also appropriate for risk-informed PBE, and (2) to determine a new risk-based return period for Risk Category IV. The use of data for wind directionality factor, Kd , which has become available from recent wind tunnel tests, revealed that reliabilities associated with wind load combinations for Risk Category II structures are, in fact, consistent with the reliabilities associated with the ASCE 7 gravity load combinations. This paper shows that the new wind maps in ASCE 7-16, which are based on return periods of 300, 700, 1,700, and 3,000 years for Risk Categories I, II, III, and IV, respectively), achieve the reliability targets in Section 1.3.1.3 of ASCE 7-16 for nonhurricane wind loads.