Title: Methodology for Development of Physics-Based Tsunami Fragilities
Authors: Attary, N., J. van de Lindt, V.U. Unnikrishnan, A.R. Barbosa, and D.T. Cox. (2016)
Journal: ASCE Journal of Structural Engineering ST.1943-541X.0001715
Tsunamis affect coastal regions around the world, resulting in fatalities and catastrophic damage to communities. Fragility functions form the basis of most risk and resilience analyses at the individual structure level, thereby allowing physical infrastructure components to be included at the community level. For tsunami loading, the vast majority of fragilities that have been developed are based on postevent observations in the field, which are usually specific to the site of the event. In this paper, a methodology to generate physics-based tsunami fragility functions is proposed, using vector intensity measures, such as tsunami flow depth and flow velocity and several combinations thereof. The proposed methodology relies on Monte Carlo Simulation for consideration of material uncertainties and includes epistemic uncertainties in the tsunami force calculation. The ability of different tsunami intensity measures (flow depth, flow velocity, and momentum flux), which are common in the literature, to predict the response of structures are investigated, and a new intensity measure (kinematic moment of momentum flux) that represents overturning moment of a structure for tsunami fragility curves is proposed. The methodology is illustrated using an application example consisting of a steel moment frame structure and fragility functions based on the kinematic moment of momentum flux are presented and shown to be a better predictor with less epistemic uncertainty.
Keywords: Tsunami fragility; Momentum of momentum flux; Physics-based fragility; Tsunami intensity measure; Monte Carlo simulation; Structural safety and reliability
Title: Integrating engineering outputs from natural disaster models into a dynamic spatial computable general equilibrium model of Centerville
Authors: Cutler, H., M. Shields, D. Tavani and S. Zahran. (2016)
Journal: Sustainable and Resilient Infrastructure
A dynamic spatial computable general equilibrium (DSCGE) model is constructed that describes how engineering and economic models can be integrated to assess the economic, demographic, and fiscal impacts of disasters. This paper has two objectives. First, we introduce the DSCGE model and describe how it is calibrated specifically for Centerville. Second, to demonstrate the analytic flexibility of the DSCGE platform, we present economy-wide prompt effects from simulations involving spatially circumscribed shocks to Centerville's building portfolio and transportation infrastructure, and then detail dynamic economy-wide effects from simulations involving combinations of infrastructure damage and adjustments to the economic behavior of agents. We conclude with a discussion of the technical challenges ahead.
Keywords: Computable general equilibrium model natural disasters infrastructure
Title: Hurricane surge-wave building fragility methodology for use with the HAZUS-MH
Authors: Do, T., J.W. van de Lindt, D.T. Cox. (2019)
Journal: Journal of Structural Engineering
Physics-based fragilities for damage, loss, and resilience analysis are needed to model a community to earthquakes, hurricane winds, tornados, or floods. Currently, most building flood fragilities such as those available in assessment tools such as HAZUS-MH do not account for the hydrodynamic forces caused by surge and waves, only the depth of a flood. In this paper, a methodology to evaluate forces on all building components including windows, doors, walls, and floor systems for elevated coastal buildings under a combination of hurricane surge and waves is proposed. The model was validated by comparing vertical and horizontal forces from existing laboratory test results of a one-tenth-scale elevated structure under wave loading. A full-scale wood-frame residential building was then modeled as an example to illustrate the method and is intended to be representative of an elevated coastal structure in a typical coastal region of the United States. The hurricane was modeled as a combination of two intensity parameters, namely significant wave height and surge level at the building location and is better able to represent the loading condition and thus damage to the structure than static flood alone. Fragility surfaces for four damage states for the building as a whole were generated as a damage combination of all damageable building components. Finally, a comparison of the loss estimated using the fragility surfaces versus the current loss model in HAZUS-MH is provided to illustrate the effect on loss estimates when including wave height in predicting damage for near-coast buildings under hurricane wave and surge. By calibrating the physics-based fragilities with empirical data, the surface fragilities developed in this paper are ready to use in HAZUS-MH or other loss and resilience-focused analysis at the community level for coastal communities subjected to both waves and storm surge during hurricanes.
Keywords: Building component fragility, Hurricane wave and surge, Elevated coastal structures, HAZUS-MH
Title: The Centerville Virtual Community: a fully integrated decision model of interacting physical and social infrastructure systems
Authors: Ellingwood, B.R., H. Cutler, P. Gardoni, W.G. Peacock, J.W. van de Lindt, and N. Wang. (2016)
Journal: Sustainable and Resilient Infrastructure
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.
Keywords: Civil infrastructure, life cycle engineering, natural hazards, resilience, risk-informed decision
Title: Modeling the resilience of critical infrastructure: the role of network dependencies
Authors: Guidotti, R., H. Chmielewski, V. Unniskrishnan, P. Gardoni, T. McAllister, and J. van de Lindt. (2016)
Journal: Sustainable and Resilient Infrastructure
Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communitiesÕ well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure.
Keywords: Resilience of infrastructure systems, network dependencies , network reliability analysis, network functionality metrics, system recovery time
Title: Network reliability analysis with link and nodal weights and auxiliary nodes
Authors: Guidotti, R., P. Gardoni, P, and Y. Chen. (2016)
Journal: Structural Safety
Networks are omnipresent, with examples in many different fields, from biological networks (such as the nervous and cardiovascular system) to physical networks (such as roadways, railways, and electrical power and water supply systems) to technological networks (such as the World Wide Web) and social network (such as the community network among people or animals). This paper proposes a novel probabilistic methodology to quantify the network reliability based on existing (diameter and efficiency) and new (eccentricity and heterogeneity) measures of connectivity that incorporate link and nodal weight sand auxiliary nodes. Nodal and link weights are introduced to take into account the importance of the components in the topology-based network model. Unweighted auxiliary nodes, locally refining the net-work model, allow one to capture the complexity of the connections between weighted end-nodes. The formulation presented in this paper is general and applicable to networks in different fields. The paper illustrates the implementation of the proposed formulation considering a transportation network subject to seismic excitation.
Keywords: System reliability, Networks analysis, Measures of connectivity, Transportation network
Title: Evaluation of an alternative seismic design approach for rigid wall flexible wood roof diaphragm buildings through probabilistic loss estimation and disaggregation
Authors: Koliou, M., van de Lindt, J.W., and Filiatrault, A. (2016)
Journal: Engineering Structures
Rigid Wall Flexible roof Diaphragm (RWFD) buildings, commonly referred to as Òbig-boxÓ buildings are the most prevalent type of construction for low-rise industrial and warehouse facilities in the United States (US). These buildings usually incorporate rigid-in plane concrete tilt-up walls and flexible wood roof diaphragms, which is a commonly seen construction technique in the Western United States. Due to their vulnerability in high seismic areas (e.g. California) observed in past earthquakes, an alternative design methodology was introduced in the FEMA P1026 document to account for the response of the flexible roof diaphragm. The FEMA P1026 design approach has been validated through numerical collapse assessment studies. In this study, the Performance-Based Earthquake Engineering framework, introduced by the Pacific Earthquake Engineering Research (PEER) center, is combined with Monte Carlo Simulation to evaluate, in a probabilistic sense, the earthquake-induced economic losses for these structures. The results are presented in terms of expected losses for two hazard intensities: Maximum Considered Earthquake (MCE) and Design Earthquake (DE), while loss disaggregation plots for collapse and no-collapse losses are also presented. The results demonstrate the ability of the FEMA P1026 design approach to reduce earthquake losses compared to current code-conforming RWFD buildings. Additionally, the results can provide damage and loss information for modeling of these types of buildings within a resilient community and other spatially focused analyses.
Keywords: Probabilistic loss assessment, Performance-based engineering, Fragility curves, Nonlinear time history analysis, Flexible wood roof diaphragm, Tilt-up walls, Seismic design provisions
Title: A decision model for intergenerational life-cycle risk assessment of civil infrastructure exposed to hurricanes under climate change
Authors: Lee, J.Y. and B.R. Ellingwood. (2016)
Journal: Reliability Engineering & System Safety
Public awareness of civil infrastructure performance has increased considerably in recent years as a result of repeated natural disasters. Risks from natural hazards may increase dramatically in the future, given current patterns of urbanization and population growth in hazard-prone areas. Risk assessments for infrastructure with expected service periods of a century or more are highly uncertain, and there is compelling evidence that climatology will evolve over such intervals. Thus, current natural hazard and risk assessment models, which are based on a presumption of stationarity in hazard occurrence and intensity, may not be adequate to assess the potential risks from hazards occurring in the distant future. This paper addresses two significant intergenerational elementsÐthe potential impact of non-stationarity in hazard due to climate change and intergenerational discounting practicesÐthat are essential to provide an improved decision support framework that accommodates the needs and values of future generations. The framework so developed is tested through two benchmark problems involving buildings exposed to hurricanes.
Keywords: Civil infrastructure, Climate change, Discounting, Engineering decision analysis, Hurricanes, Reliability, Structural engineering
Title: Building portfolio fragility functions to support scalable community resilience assessment
Authors: Lin, P. and N. Wang. (2016)
Journal: Sustainable and Resilient Infrastructure
Community resilience planning, risk mitigation, and recovery optimization must assume a system perspective at the level of the overall community built environment. While engineers can quantify the performance of individual buildings and facilities, such information must be aggregated to reflect the vulnerability of the building portfolio as a whole to support resilience-based decisions at the community level. This study presents a methodology for building portfolio analysis that relates the performance of individual buildings exposed to natural hazards to the overall performance of a building portfolio. We introduce the concept of building portfolio fragility function (BPFF), defined as the probability that a building portfolio, as an aggregated system, fails to achieve prescribed performance objectives conditioned on scenario hazards, to characterize the vulnerability of a building portfolio and to directly inform resilience-driven decisions at the community level. The paper concludes with an illustration of the development of BPFFs to the Centerville community.
Keywords: Community resilience, portfolio fragility function, risk, spatial correlation, system performance objectives
Title: A risk de-aggregation framework that relates community resilience goals to building performance objectives
Authors: Lin, P.H., N. Wang, and B.R. Ellingwood. (2016)
Journal: Sustainable and Resilient Infrastructure
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.
Keywords: Buildings (codes), civil infrastructure, community resilience, natural hazards, performance-based engineering, risk assessment, structural engineering
Title: Optimal network flow: A predictive analytics perspective on the fixed-charge network flow problem
Authors: Nicholson, C. and W. Zhang. (2016)
Journal: Computers & Industrial Engineering
The fixed charge network flow (FCNF) problem is a classical NP-hard combinatorial problem with widespread applications. To the best of our knowledge, this is the first paper that employs a statistical learning technique to analyze and quantify the effect of various network characteristics relating to the optimal solution of the FCNF problem. In particular, we create a probabilistic classifier based on 18 network related variables to produce a quantitative measure that an arc in the network will have a non-zero flow in an optimal solution. The predictive model achieves 85% cross-validated accuracy. An application employing the predictive model is presented from the perspective of identifying critical network components based on the likelihood of an arc being used in an optimal solution.
Keywords: Network analysis, Fixed charge network flow, Predictive modeling, Critical components
Title: Probabilistic assessment of near-field tsunami hazards: Inundation depth, velocity, momentum flux, arrival time, and duration applied to Seaside, Oregon
Authors: Park, H., and D. T. Cox. (2016)
Journal: Coastal Engineering
The generation, propagation and inundation for a probabilistic near-field tsunami hazards assessment (PTHA) at the Cascadia Subduction Zone (CSZ) are analyzed numerically. For the tsunami hazard assessment, a new method is presented to characterize the randomness of the fault slip in terms of the moment magnitude, peak slip location, and a fault slip shape distribution parameterized as a Gaussian distribution. For the tsunami inundation resulting from the seismic event, five tsunami intensity measures (IMs) are estimated: (1) the maximum inundation depth, h max, (2) the maximum velocity, V Max,(3) the maximum momentum flux, MMax, (4) the initial ar-rival time exceeding a 1 m inundation depth, TA, and (5) the duration exceeding a 1 m inundation depth, Th, and presented in the form of annual exceedance probabilities conditioned on a full-rupture CSZ event. The IMs are generally observed to increase as the moment magnitude increases, as the proximity of the peak slip becomes closer to the study area, and as the distribution of fault shape narrows. Among the IMs, the arrival time (TA)shows a relatively weak sensitivity to the aleatory uncertainty while the other IMs show significant sensitivity, especially MMax. It is observed at the shoreline that MMax increases by an order of magnitude from the 500-yearto the 1000-year event, while h max increases by a factor of 3, and TA decreases by only factor of 0.05. The intensity of IMs generally decreases inland, but there are also varying dependencies on bathymetry. For example, a shorter inundation duration, Th (b10 min) is observed at the higher ground level (zN3m) while a longer Th (~100 min) is observed near the river and creek.
Keywords: Cascadia Subduction Zone, Near-field tsunami, Aleatory uncertainty, Resilience, Intensity measures, Probabilistic tsunami hazard assessment
Title: Probabilistic seismic and tsunami damage analysis (PSTDA) of the Cascadia Subduction Zone applied to Seaside, Oregon
Authors: Park, H., M.S. Alam, D.T. Cox, A.R. Barbosa, and J.W. van de Lindt. (2019)
Journal: International Journal of Disaster Risk Reduction
This study presents a probabilistic seismic and tsunami damage analysis (PSTDA) due to both earthquake shaking and tsunami inundation from tsunamigenic earthquake events at a coastal community. In particular, this study evaluates the annual exceedance probability (AEP) of seismic and tsunami hazards through earthquake and tsunami modeling that share the same fault sources. Then, estimates of earthquake and tsunami impact on the built environment utilizing fragility functions is predicted spatially. The PSTDA evaluates the combined impacts of earthquake and tsunami through a stochastic approach that accounts for the accumulated damage due to seismic shaking and subsequent tsunami inundation. A case study is setup and applied to Seaside, Oregon, for tsunamigenic earthquake events originating from the Cascadia Subduction Zone (CSZ) in order to illustrate the application of the PSTDA evaluation framework. The PSTDA integrates as a step within a resilience-focused risk-informed decision making process, which includes the assessment of direct and indirect socio-economic losses due to tsunamigenic earthquake events.
Keywords: Earthquake damage, Multi-hazard, Probabilistic seismic and tsunami damage analysis (PSTDA), Tsunamigenic, Tsunami damage
Title: Using artificial neural networks to forecast economic impact of multi-hazard hurricane-based events
Authors: Pilkington, S. and H. Mahmoud. (2016)
Journal: Sustainable and Resilient Infrastructure
In multi-hazard events, it remains difficult to communicate the collective effect these hazards have on the envisioned outcome or impact to the public. Currently, there are multiple models in use by emergency management and other government personnel to predict effects of hazards that put emphasis on wind damage (just as the Saffir–Simpson scale does), which tend to leave out the non-wind driven precipitation hazard. Experts who work with hazard events consistently build a knowledge base over time from experience that accounts for the collective effects of these multiple hazards in relation to locational vulnerabilities. In this study, an original artificial neural network is developed and used in an effort to mimic the previously mentioned learned and experienced-based knowledge. The output from the neural network model is an Impact Level Ranking System that ranks hurricanes based on total economic damage. The use of population affected, landfall location(s), wind speed, pressure, storm surge, and precipitation for inputs with a final Bayesian Regulation training approach allows for an ability to forecast multi-hazard hurricane events in terms the public could comprehend while remaining thorough in all hazards.
Keywords: Hurricane, neural network, economic damage, impact prediction, risk, vulnerability
Title: Probabilistic framework for performance assessment of electrical power networks to tornadoes
Authors: Unnikrishnan, V.U. and J.W. van de Lindt. (2016)
Journal: Sustainable and Resilient Infrastructure
The Electrical Power Network (EPN) constitutes a vital component of the nation’s critical infrastructure. Additionally, the resilience of the community to different natural and man-made hazards depends upon the reliability of the EPN. In this study, a probabilistic methodology is proposed for the performance assessment of EPN subject to tornadoes. The proposed methodology can be disaggregated into distinct analysis phases: hazard analysis, EPN characterization, hazard-network characterization, network analysis, and loss analysis. A hypothetical community with EPN is used to illustrate the methodology. Multi-layer Monte Carlo Simulation together with fragility functions of the components is used to calculate the probability of exceedance of the repair cost and time, to restore power to selected nodes. The methodology presented herein thus provides the ability to statistically characterize and model restoration for a given topology at a detailed enough level to be able to model dependency and potential interdependencies using mechanistic approaches.
Keywords: Electrical power networks, tornado hazard, Monte Carlo simulation, hazard-network interaction, network analysis
Title: A multi-objective optimization model for retrofit strategies to mitigate direct economic loss and population dislocation
Authors: Zhang, W. and C. Nicholson. (2016)
Journal: Sustainable and Resilient Infrastructure
One strategy to mitigate social and economic vulnerabilities of communities to natural disasters is to enhance the current infrastructure underlying the community. Decisions regarding allocation of limited resources to improve infrastructure components are complex and involve various trade-offs. In this study, an efficient multi-objective optimization model is proposed to support decisions regarding building retrofits within a community. In particular, given a limited budget and a heterogeneous commercial and residential building stock, solutions to the proposed model allow a detailed analysis of the trade-offs between direct economic loss and the competing objective of minimizing immediate population dislocation. The developed mathematical model is informed by earthquake simulation modeling as well as population dislocation modeling from the field of social science. The model is applied to the well-developed virtual city, Centerville, designed collaboratively by a team of engineering experts, economists, and social scientists. Multiple Pareto optimal solutions are computed in the case study and a detailed analysis regarding the various decision strategies is provided.
Keywords: Community resilience, multi-objective optimization, hazard mitigation, population dislocation
Title: Resilience-based post-disaster recovery strategies for road-bridge networks
Authors: Zhang, W., N. Wang, and C. Nicholson. (2016)
Journal: Structure and Infrastructure Engineering 1-10
This paper presents a novel resilience-based framework to optimise the scheduling of the post-disaster recovery actions for road-bridge transportation networks. The methodology systematically incorporates network topology, redundancy, traffic flow, damage level and available resources into the stochastic processes of network post-hazard recovery strategy optimisation. Two metrics are proposed for measuring rapidity and efficiency of the network recovery: total recovery time (TRT) and the skew of the recovery trajectory (SRT). The TRT is the time required for the network to be restored to its pre-hazard functionality level, while the SRT is a metric defined for the first time in this study to capture the characteristics of the recovery trajectory that relates to the efficiency of those restoration strategies considered. Based on this two-dimensional metric, a restoration scheduling method is proposed for optimal post-disaster recovery planning for bridge-road transportation networks. To illustrate the proposed methodology, a genetic algorithm is used to solve the restoration schedule optimisation problem for a hypothetical bridge network with 30 nodes and 37 bridges subjected to a scenario seismic event. A sensitivity study using this network illustrates the impact of the resourcefulness of a community and its time-dependent commitment of resources on the network recovery time and trajectory.
Keywords: Decision optimisation, network recovery, resilience, restoration schedule, transportation networks, uncertainty modelling
Title: Development of Physics-based Tsunami Fragility Functions Considering Structural Member Failures
Authors: Alam, M.S., A.R. Barbosa, M.H. Scott, D.T. Cox, and J.W van de Lindt. (2017)
Journal: ASCE Journal of Structure Engineering
A probabilistic framework is presented for the development of physics and simulation-based parametrized tsunami fragility functions for structures accounting for structural member failures. The proposed framework is general and accounts for material and geometric sources of uncertainty and makes use of nonlinear finite-element structural models and the first-order second-moment (FOSM) reliability method. The application of the framework is illustrated with the development of parametrized fragility functions for an example reinforced concrete moment frame building designed to recent United States codes. Results indicate that explicit consideration of structural member failures is of paramount importance because the fragility functions based on global failure criteria that do not account for member failures tend to overpredict damage state capacities. Among the several sources of uncertainty considered, breakaway openings in the building are the dominant contributor to the uncertainty in the structural capacity. In addition, the estimation efficiency of several scalar and vector-valued intensity measures as predictors of structural damage is evaluated using the logistic regression method. The intensity measures considered consist of inundation depth, flow velocity, specific momentum flux, kinematic moment of specific momentum flux, and their interactions. The estimation efficiency of vector-valued intensity measures is found to be higher than that of scalar intensity measures. Among the scalar intensity measures analyzed, those that combine information of inundation depth and flow velocity are identified to be the most efficient predictors of structural damage, and therefore are considered to be the preferred measures to characterize the intensity of tsunami hazards for practical applications.
Keywords: Drag force; Logistic regression; Parametrized fragility functions; Reinforced concrete moment frame; Simulation models
Title: Performance-Based Tsunami Engineering Methodology for Risk Assessment of Structures
Authors: Attary, N., V. Unnikrishnan, J. van de Lindt, D.T. Cox, and A. Barbosa. (2017)
Journal: Engineering Structures
Tsunamis are rare destructive phenomena caused by the sudden displacement of a large amount of water in the ocean and can result in enormous losses to coastal communities. The resilience of coastal communities to tsunamis can be improved through the use of risk-informed decision making tools. Performance- Based Engineering (PBE) approaches have been developed for different natural hazards including earthquake, fire, hurricane, and wind to perform probabilistic risk assessment for structures. In this study, a probabilistic Performance-Based Tsunami Engineering (PBTE) framework based on the total probability theorem is proposed for the risk assessment of structures subject to tsunamis. The proposed framework can be disaggregated into the different basic analysis phases of hazard analysis, foundation and structure characterization, interaction analysis, structural analysis, damage analysis, and loss analysis. An application example consisting of the risk assessment of a three-story steel moment frame structure was performed using the proposed framework. The probability of exceedance of the total replacement cost including structural, nonstructural, and content losses were computed.
Keywords: Tsunami Performance-Based Engineering, Loss analysis, Hybrid fragilities, Monte Carlo simulation
Title: Research of long-span bridge and traffic system subjected to winds: a system and multi-hazard perspective
Authors: Chen, S., Y. Zhou, G. Hou, F. Chen, and J. Wu (2017)
Journal: International Journal of Transportation Science and Technology
Wind effects on long-span bridges and moving vehicles have drawn considerable attention during the past years. Effectively considering the dynamic interactions between wind, vehicles and bridges and rationally assessing the bridge performance becomes essential to this type of critical infrastructure system. The impact of strong winds on long-span bridge transportation systems has received a lot of attention during the past decades. Meanwhile, low to moderate winds may serve as a type of important service load acting on the long-span bridge transportation system, along with other extreme or hazardous loads. In addition to the structural integrity, it is also important to appropriately assess the vehicle performance, such as safety and comforting issues, under wind so that the associated risks can be identified and mitigated. This paper summarizes some recent advances on the research of wind effects on long-span bridge and traffic systems with a focus on the efforts from a system and multi-hazard perspective.
Keywords: Long-span bridge, Traffic flow, Wind, Safety, Resilience
Title: Measuring and enhancing resilience of building portfolios considering the functional interdependence among community sectors
Authors: Feng, K., N. Wang, Q. Li, and P. Lin. (2017)
Journal: Structural Safety
Resilience is an attribute of communities, and is supported by community building sectors (occupancy types) with different functionalities. Evaluating community resilience and functionality requires the establishment of new metrics and their quantification. This study introduces a methodology to consider how the interdependencies in functionality among different building sectors impact community resilience. Four building sectors that provide essential functions to a community, i.e. housing, education, business and public services, are considered. The percentage of people in a community who dislocate following a disaster as a result of the physical damages to buildings is selected as the resilience metricin this conceptual study. A framework is further developed to determine the optimum strategies for retrofitting community building portfolios as a whole in order to achieve an overall community resilience objective expressed in terms of the threshold value of the community resilience metric identified above. Finally, the methodology to quantify community functionality and the associated retrofit optimization algorithm are illustrated using a simplified hypothetical community building portfolio in China exposed to potentially severe earthquakes, in which the objective is to achieve a predetermined functionality level when financial constraints may be present.
Keywords: Building inventory, Building retrofit, Community functionality, Community resilience, Interdependency, Optimization
Title: Multiple-Hazard Fragility and Restoration Models of Highway Bridges for Regional Risk and Resilience Assessment in the United States: State-of-the-Art Review
Authors: Gidaris, I, J. E. Padgett, A. R. Barbosa, S. Chen, D.T. Cox, B. Webb and A. Cerato. (2017)
Journal: ASCE Journal of Structural Engineering
Highway bridges are one of the most vulnerable constituents of transportation networks when exposed to one or more natural hazards, such as earthquakes, hurricanes, tsunamis, and riverine floods. To facilitate and enhance prehazard and posthazard event mitigation and emergency response strategies of transportation systems and entire communities, probabilistic risk and resilience assessment methodologies have attracted increased attention recently. In this context, fragility and restoration models for highway bridges subjected to a range of hazards are essential tools for efficient and accurate quantification of risk and resilience. This paper provides a comprehensive review of state-of-the-art fragility and restoration models for typical highway bridge classes that are applicable for implementation in multihazard risk and resilience analyses of regional portfolios or transportation networks in the United States. An overview of key gaps in the literature is also presented to guide future research.
Keywords: Highway bridges; Fragility; Restoration; Multihazard; Probabilistic risk assessment; Resilience; Earthquakes; Hurricanes; Tsunamis; Riverine floods; Structural safety and reliability.
Title: Modeling resolution effects on the seismic response of a steel hospital
Authors: Hassan, E. and H. Mahmoud. (2017)
Journal: Journal of Constructional Steel Research
Numerical finite element analysis is considered a reliable tool for response assessment of structures under extreme loadings. When developing finite element models, various geometrical and behavioral assumptions are typically made to simplify the modeling approach and to save on computational cost. The effect of these assumptions on analysis results, however, could be substantial and might significantly alter the decisions pertaining to design, assessment, or retrofit of the structure considered. The importance of accurate modeling, particularly of critical infrastructures, can be vital for post-disaster recovery management following an extreme event. In this study, the seismic response of a six-story hospital building with buckling-restrained braces, located in Memphis, Tennessee, is evaluated for different modeling resolution levels. Different pushover and non-linear time-history analyses are conducted to understand, compare, and evaluate the seismic performance of the structure using both 2-D and 3-D numerical models with and without soil. Various nonlinear features are considered in the simulations including realistic hysteretic behavior of the connections, buckling-restrained braces, and soil-foundation-structure interaction. The results highlight the importance of including representative member and connection models as well as realistic boundary conditions, while employing 3-D simulations, for accurate predictions of system response.
Keywords: 3-D modeling, Braced frames, Buckling-restrained braces, Incremental dynamic analysis, Model resolution, Soil-structure interaction
Title: Framework of microscopic traffic flow simulation on highway infrastructure system under hazardous driving conditions.
Authors: Hou, G., S. Chen, Y. Zhou, and J. Wu. (2017)
Journal: Journal of Sustainable and Resilient Infrastructure
A typical highway system includes infrastructures, such as roadways and bridges, and moving traffic flow. The resilience of a highway system subjected to various hazards depends on not only post-hazard integrity of infrastructure, but also safe and smooth movements of vehicles through the system during and immediately following hazards. To rationally predict the post-hazard performance of a highway system including both structural integrity and traffic functionality, an advanced traffic flow simulation tool of a highway system under hazardous conditions is needed. A new cellular automaton (CA)-based traffic flow simulation framework is developed for the traffic flow simulation on a typical highway system including a long-span bridge under hazardous conditions by incorporating limited deceleration rate, anticipation effect, realistic vehicle properties, and different driving behaviors. A demonstrative study is carried out with the proposed framework to investigate the traffic flow characteristics and potential impacts on both infrastructure performance and vehicle safety.
Keywords: Cellular automaton (CA), traffic flow, hazardous condition, highway system, post-hazard performance, resilience
Title: Parameterized Fragility Assessment of Bridges Subjected to Pier Scour and Vehicular Loads
Authors: Kameshwar, S. and J. E. Padgett. (2017)
Journal: Journal of Bridge Engineering
Even though scour-related bridge failures are among the most common causes of bridge failure, the literature lacks studies that have assessed the safety of scoured bridges to carry vehicular loads. As a result, bridge owners often rely on subjective limits of scour depth triggering closure or load limitations. This study focused on developing fragility functions for bridges subjected to pier scour under vehicular loads. For this purpose, fragility functions parameterized on bridge details, scour depth, and vehicular loads were developed to aid management of traffic on scoured bridges and prevent life-threatening accidents. Instability caused by vehicle-induced loads (i.e., vertical gravity loads and longitudinal loads from vehicle braking) was considered. Therefore, failures resulting from lack of bearing capacity and failure of bridge columns, abutments, and bearings as a result of braking loads were studied. To obtain the fragility functions for these failure modes, a set of 3,500 bridge parameter combinations was generated using Latin hypercube sampling (LHS). For all bridge parameter combinations, bridges were modeled in OpenSees, and finite-element analyses were performed to assess the stability of scoured bridges under vehicular loads. The results show that bridges with pier scour are more vulnerable to bearing failure than to failure from longitudinal braking loads. These analysis results were used to develop fragility functions using logistic regression, which were tested on two bridges in New Zealand. To facilitate application of the fragility functions for practical scenarios where multiple soil layers are present, this study developed a soil homogenization procedure. The fragility functions and the soil homogenization procedure were used to study the performance of a case study bridge in Brazoria County, Texas. The results for the case study bridge show the effects of variation in vehicular load, position of the vehicle, and bridge parameters on the fragility of the bridge, highlighting the usefulness of the fragility functions to support decisions on imposing load and lane restrictions and to study the effects of parameter variation on the performance of bridges with pier scour.
Title: Performance Assessment of Tilt-Up Big-Box Buildings Subjected to Extreme Hazards: Tornadoes and Earthquakes
Authors: Koliou, M., H. Masoomi, and J.W. van de Lindt. (2017)
Journal: ASCE Journal of Performance of Constructed Facilities
This paper investigates the response of tilt-up (referred to as "big-box") buildings subjected to two extreme hazards to which they have been observed to be susceptible—high winds (tornadoes) and earthquakes—through a performance assessment methodology utilizing fragility analysis. The methodology focuses on load characterization, defining performance goals and corresponding limit states, and assess- ing performance through fragility analysis. Performance goals and limit states accounting for the performance of big-box buildings during past tornado and earthquake events in the United States are identified, as are research findings reported in the literature. The proposed methodology is applied to a set of four big-box buildings representative of the current building stock in the United States, i.e., building archetypes. The building archetypes incorporate concrete tilt-up wall panels and in-plane flexible roof diaphragms that vary in size, plan aspect ratios, and roof diaphragm connectors. The results of this study show that the building size (footprint) significantly affects the performance of big-box buildings subjected to tornado wind loads but the roof connector variability does not influence the building response, given that the roof joists failed before the roof decks connections. In contrast, the performance of big-box buildings subjected to earthquake loading is highly associated with the roof diaphragm connectors used in the design phase, which are the main source of inelasticity in the roof system.
Keywords: Fragility analysis, Performance assessment, Wind/Tornado loads, Seismic loads, Tilt-up buildings
Title: State of the Research in Community Resilience: Progress and Challenges
Authors: Koliou, M., J.W. van de Lindt, T.P. McAllister, B.R. Ellingwood, M. Dillard, and H. Cutler. (2017)
Journal: Sustainable and Resilient Infrastructure
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.
Keywords: Community resilience, critical infrastructure, computable general equilibrium economic models, disaster recovery, social systems
Title: Stochastic post-disaster functionality recovery of community building portfolios I: Modeling
Authors: Lin, P. and N. Wang. (2017)
Journal: Structural Safety
Understanding the process of post-disaster recovery is a critical step toward assessing and achieving community resilience. However, the recovery process of a community building portfolio as a spatially distributed system is intrinsically complex and highly uncertain, and is conditional on the resourcefulness and social-economic characteristics of the community as well as the various decisions made by numerous community stakeholders and building owners at different phases of the recovery. We propose a simulation-based building portfolio recovery model (BPRM) to predict the functionality recovery tim eand recovery trajectory of a community building portfolio following natural scenario hazard events, in two steps: (1) modeling individual building-level restoration as a discrete state, continuous time Markov Chain (CTMC); and (2) modeling building portfolio-level recovery through aggregating the CTMC restoration processes of individual buildings across the domain of the community and over the entire recovery time horizon. We propagate uncertainties associated with the recovery process in a consistent manner in order to quantify portfolio recovery metrics probabilistically. The proposed building portfolio recovery model is intended to support risk-informed community resilience planning and hazard mitigation.
Keywords: Recovery modeling, Building portfolio, Functionality state, Building restoration, Continuous time Markov Chain, Community resilience
Title: Stochastic post-disaster functionality recovery of community building portfolios II: Application
Authors: Lin, P. and N. Wang. (2017)
Journal: Structural Safety 10.1016/j.strusfe.2017.05.004
Part I of this two-part paper introduced a building portfolio recovery model (BPRM) to forecast the stochastic recovery process of building portfolios within a community following an extreme hazard event. The BPRM models’ restoration of individual building-level functionalities as a discrete state, continuous time Markov Chain, while it models portfolio-level recovery by aggregating the building-level restoration processes in both temporal and spatial dimensions. In this paper, we illustrate the implementation of the BPRM to project the building portfolio recovery of a mid-size community following a predefined scenario earthquake. The recovery analysis integrates the engineering process of building reconstructions with available community resources and social-economic characteristics of different population groups. The spatial variations in recovery speed in different residential zones within the com-munity reflect the disparities in resourcefulness and recoverability of homeowners with different social and economic status. In addition, sensitivity studies are performed to investigate the capability of the BPRM to quantify the impact of candidate pre-disaster mitigation strategies on the building portfolio recovery time and trajectory, illustrating the potential use of the BPRM in supporting risk-informed com-munity resilience planning.
Keywords: Recovery modeling, Building portfolio, Functionality state, Building restoration, Continuous time Markov Chain, Community resilience
Title: A Probabilistic Cellular Automata Framework for Assessing the Impact of WUI Fires on Communities
Authors: Mahmoud, H. and A. Chulahwat. (2017)
Journal: Procedia Engineering
The 'wildland–urban interface' (WUI) is a term commonly used to describe areas where wildfires and the built environment have the potential to interact resulting in loss of properties and potential loss of life.  Significant residential losses associated with wildland interface fires have occurred worldwide in recent years and substantial research has been conducted on developing numerical models of ignition due to convection and ember attacks.  These studies provide substantial insight into the behaviour and growth of wildland fires, which have been further utilized to build fire exposure rating of structures.  The FireWise program in the United States and the FireSmart manual in Canada are two key examples of provisions developed for determining fire exposure ratings for a structure.  While previous studies provide significant contribution to modelling fire propagation, a much more comprehensive model is required, which would encompass all the key variables associated with WUI fires.  This paper aims at extending previously conducted efforts by developing a simulation-based model.  A typical fire propagation simulation requires solving the coupled fluid-thermal differential equations which results in extreme run times making it unsuitable for general purposes, however the model in this study utilizes theory of cellular automata, which reduces the processing times substantially by simplifying the underlying equations involved. Cellular automata utilize a specific set of rules to model propagation by convection as well as ember travel. In addition, the model also considers key parameters such as humidity, nature of vegetation and topology while evaluating the propagation paths. Due to the flexible nature of the model its accuracy can be tuned to a certain extent by optimizing the propagation rules using real-event data
Keywords: WUI Fire, Cellular Automata, Probabilistic model
Title: Determining Mean Recurrence Intervals for Updated Wind Maps in ASCE 7-16.
Authors: McAllister, T., N. Wang, and B.R. Ellingwood. (2017)
Journal: ASCE Journal of Structural Engineering
ASCE Standard 7 is moving toward load requirements that are consistent with reliability-based design goals characteristic of performance-based engineering (PBE). As part of this move, reliability analyses were conducted using updated wind data to determine wind speed return periods necessary to meet the target reliability goals currently found in ASCE 7. A key part of this analysis was a re-examination of the role played by wind directionality on structural reliability. Analyses of wind load combinations in the early 1980s conducted to support the first-generation of strength load combinations in ANSI A58/ASCE 7 determined member reliabilities that apparently were lower than those for gravity load combinations, creating a controversy that up to this time has not been resolved. Using a wind directionality factor based on recent research leads to increased reliabilities for wind load combinations. Adoption of the new wind maps in ASCE 7 at the recommended return periods will achieve wind load reliabilities that are comparable reliability to those for gravity load criteria in extratropical regions. The recommended wind map return periods are 300, 700, 1700, and 3000 years for Category I, II, II and IV, respectively.
Keywords: wind, directionality, design, return period, reliability
Title: Probabilistic Seismic and Tsunami Hazard Analysis (PSTHA) Conditioned on a Megathrust Rupture of the Cascadia Subduction Zone
Authors: Park, H., D. T. Cox, M.S. Alam, and A.R. Barbosa. (2017)
Journal: Frontiers in the Built Environment
This paper presents a methodology for probabilistic hazard assessment for the multi-hazard seismic and tsunami phenomena [probabilistic seismic and tsunami hazard analysis (PSTHA)]. For this work, a full-rupture event along the Cascadia subduction zone is considered and the methodology is applied to a study area of Seaside, Oregon, which is located on the US Pacific Northwest coast. In this work, the annual exceedance probabilities (AEPs) of the tsunami intensity measures (IMs) are shown to be qualitatively dissimilar to the IMs of the seismic ground motion in the study area. Specifically, the spatial gradients for the tsunami IM are much stronger across the length scale of the study area owing to the physical differences of wave propagation and energy dissipation of the two mechanisms. Example results of probabilistic seismic hazard analysis and probabilistic tsunami hazard analysis are shown for three observation points in the study area of Seaside. For the seismic hazard, the joint mean annual rate of exceedance of IMs shows similar trends for the three observation points, even though for a given observation point there is a large scatter between two ground-motion IMs analyzed, which were peak ground acceleration (PGA) and spectral acceleration at a period of vibration of 0.3 s, i.e., PGA and Sa (T1= 0.3 s). For the tsunami hazard, the joint AEP of maximum flow depth (hmax) and maximum momentum flux ((MF)max) shows a high correlation between the two IMs in the study area. The joint AEP at each of the three observation points follows a particular Froude number (Fr) due to the local site-specific conditions rather than the distributions of fault slip distributions used to generate the scenarios that are the basis of the AEP maps developed. The joint probability distribution of hmax and (MF)max throughout the study region falls between 0.1 ≤ Fr < 1.0 (i.e., the flow is subcritical), regardless of return interval (500-, 1,000-, and 2,500-year). However, the peak of the joint probability distribution with respect to hmax and (MF)max varies with the return interval, and the largest values of hmax and (MF)max were observed with the highest return intervals (2,500 years) as would be expected. The results of the PSTHA can be the basis for a probabilistic multi-hazard damage and loss assessment and help to evaluate the uncertainties of the multi-hazard assessments.
Keywords: seismic hazard analysis, tsunami hazard analysis, multi-hazard risk, Cascadia subduction zone, community resilience
Title: Comparison of inundation depth and momentum flux based fragilities for probabilistic tsunami damage assessment and uncertainty analysis
Authors: Park, H., D. T. Cox, and A. Barbosa. (2017)
Journal: Coastal Engineering
Annual exceedance probabilities of the maximum tsunami inundation depth, hMax, and momentum flux, MMax, conditional on a full-rupture event of the Cascadia Subduction Zone (CSZ) were used to estimate the probability of building damage using a fragility analysis at Seaside, Oregon. Tax lot data, Google Street View, and field reconnaissance surveys were used to classify the buildings in Seaside and to correlate building typologies with existing fragility curves according to the construction material, number of stories, and building seismic design level based on the date of construction. A fragility analysis was used to estimate the damage probability of buildings for 500-, 1000-, and 2500-year exceedance probabilities conditioned on a full-rupture CSZ event. Finally, the sensitivity of building damage was estimated for both the aleatory and epistemic uncertainties involved in the process of damage estimation. Probable damage estimates from the fragility curves based on hMax and on MMax both generally show higher damage probability for structures that are wooden and closer to the shoreline than those that are reinforced concrete (RC) and further landward of the shoreline. However, a relatively high and somewhat unrealistic damage probability was found at the river and creek region from the fragility curve analysis using hMax. Within 500 m from the shoreline, wood structure damage shows significant sensitivity to the aleatory uncertainty of the tsunami generation from the CSZ event. On the other hand, RC structure damage showed equal sensitivity to the aleatory uncertainty of the tsunami generation as well as the epistemic uncertainties due to the numerical modeling of the tsunami inundation (friction), the building classification (material and date of construction), and the type of fragility curves (depth or momentum flux typecurves). Further from the shoreline, the wood structures showed similar aleatory and epistemic uncertainties, qualitatively similar to the RC structure sensitivity closer to the shoreline.
Keywords: Tsunami, Cascadia Subduction Zone, Fragility curves, Building damage, Momentum flux, Disaster resilience
Title: Experimental modeling of horizontal and vertical wave forces on an elevated coastal structure
Authors: Park, H., T. Tomiczek, D.T. Cox, J.W. van de Lindt, and P. Lomonaco. (2017)
Journal: Coastal Engineering
A large-scale physical model was created in Oregon State University's Large Wave Flume to collect an extensive dataset measuring wave-induced horizontal and vertical forces on an idealized coastal structure. Water depth was held constant while wave conditions included regular, irregular, and transient (tsunami-like) waves with different significant wave heights and peak periods for each test. The elevation of the base of the test specimen with respect to the stillwater depth (air gap) was also varied from at-grade to 0.28 m above the stillwater level to better understand the effects of raising or lowering a nearshore structure on increasing or decreasing the horizontal and vertical wave forces. Results indicate that while both horizontal and vertical forces tend to increase with increasing significant wave height, the maximum and top 0.4% of forces increased disproportionally to other characteristic values such as the mean or top 10%. As expected, the horizontal force increased as the test specimen was more deeply submerged and decreased as the structure was elevated to larger air gaps above the stillwater level. However, this trend was not true for the vertical force, which was maximized when the elevation of the base of the structure was equal to the elevation of the stillwater depth. Small wave heights were characterized by low horizontal to vertical force ratios, highlighting the importance of considering vertical wave forces in addition to horizontal wave forces in the design of coastal structures. The findings and data presented here may be used by city planners, engineers, and numerical modelers, for future analyses, informed coastal design, and numerical benchmarking to work toward enabling more resilient nearcoast structures.
Keywords: Elevated structures, Horizontal force, Vertical force, Hurricane, Physical experiment, Air gap
Title: Resilience analysis: a mathematical formulation to model resilience of engineering systems
Authors: Sharma, N., A. Tabandeh, and P. Gardoni. (2017)
Journal: Sustainable and Resilient Infrastructure
The resilience of a system is related to its ability to withstand stressors, adapt, and rapidly recover from disruptions. Two significant challenges of resilience analysis are to (1) quantify the resilience associated with a given recovery curve; and (2) develop a rigorous mathematical model of the recovery process. To quantify resilience, a mathematical approach is proposed that systematically describes the recovery curve in terms of partial descriptors, called resilience metrics. The proposed resilience metrics have simple and clear interpretations, and their definitions are general so that they can characterize the resilience associated with any recovery curve. This paper also introduces a reliability-based definition of damage levels which is well-suited for probabilistic resilience analysis. For the recovery modeling, a stochastic formulation is proposed that models the impact of recovery activities and potential disrupting shocks, which could happen during the recovery, on the system state. For illustration, the proposed formulation is used for the resilience analysis of a reinforced concrete (RC) bridge repaired with fiber-reinforced polymer.
Keywords: Life-cycle analysis, recovery, reliability, resilience, stochastic
Title: An interdisciplinary system dynamics model for post-disaster housing recovery
Authors: Sutley, E. J. and S. Hamideh. (2017)
Journal: Sustainable and Resilient Infrastructure
Many previous disasters have demonstrated the need for extensive personal, public, and governmental expenditures for housing recovery highlighting the importance of studying housing recovery. Yet, much research is still needed to fully understand the multi-faceted and complex nature of housing recovery. The goal of this paper is to present a holistic model to further the understanding of the dynamic processes and interdependencies of housing recovery. The impetus for this work is that inequalities in housing recovery could be addressed more effectively if we better understood interconnected factors and dynamic processes that slow down recovery for some. Currently, there is a lack of understanding about such factors and processes. Literature from engineering and social sciences was reviewed to develop an integrated system dynamics model for post-disaster housing recovery. While it is beyond current capabilities to quantify such complexities, the presented model takes a major stride toward articulating the complex phenomenon that is housing recovery.
Keywords: Post-disaster housing recovery, system dynamics, social vulnerability, causal factors, indicators
Title: Multihazard Analysis: Integrated Engineering and Social Science Approach
Authors: Sutley, E.J., J.W. van de Lindt, and L. Peek. (2017)
Journal: ASCE Journal of Structural Engineering
Reducing the potential impacts from a future disaster can be accomplished through decreasing the hazard exposure and reducing the community’s vulnerability. Moreover, communities have both physical and social vulnerabilities that deserve attention; however, most engineering studies focus on assessing and mitigating the physical infrastructure without fully considering the social infrastructure. This paper offers a more holistic examination of vulnerability. Specifically, a two-stage analytical approach is presented that treats both an earthquake and a community’s socioeconomic and demographic makeup as hazards. The first stage addresses the physical vulnerability of a community through retrofitting the residential building stock using an inventory of woodframe building archetypes. The second stage incorporates the social characteristics of a community through modeling six social vulnerability variables. A social disaster factor (SDF) is introduced to offer a quantifiable approach for understanding the intersections between physical and social vulnerabilities. Case studies are presented for three communities: a middle-class ZIP code, the poorest ZIP code, and the wealthiest ZIP code, all in Los Angeles County, California. The SDF is computed and compared for the case studies during both stages of the analysis. The analyses demonstrate that when only physical vulner- abilities are modeled, one might incorrectly conclude that the impacts of the event are virtually eliminated. However, when social vulner- abilities are modeled as a hazard alongside the physical vulnerabilities, the projected impacts of the disaster are severe, especially for the most vulnerable populations, in terms of injuries, fatalities, posttraumatic stress disorder diagnoses, and number of dislocated households. In the combined model, these impacts run along racial and economic fault lines, with the most marginalized communities experiencing the most extreme projected losses. These results may have implications for both theory and practice.
Keywords: Woodframe buildings, Earthquake, Natural disasters, Social vulnerability, Household dislocation, Seismic effects
Title: Vulnerability and Robustness of Civil Infrastructure Systems to Hurricanes
Authors: Wang, Shuoqi and D.A. Reed. (2017)
Journal: Frontiers in the Built Environment
Civil infrastructure systems play an important role in community resilience. Without proper functioning of the infrastructure, especially power delivery, society will not recover quickly from disruptive events, such as hurricanes. In this paper, the vulnerability, response, and recovery of selected infrastructure at the system level for several hurricanes in the USA are modeled using geostatistical methods, employing post-event data. Inoperability is the main variable modeled for each infrastructure system. In this paper, robustness is a property considered to be the opposite of vulnerability, and it plays an important role in the resiliency modeling. The infrastructure systems examined in this paper are electric power delivery and telecommunications. Connections among the systems are briefly explored.
Keywords: hurricane, wind engineering, structural engineering, resilience, fragility
Title: Guidance on Conducting a Sytematic Literature Review
Authors: Xiao, Y. and Watson, M. (2017)
Journal: Journal of Planning Education and Research
Literature reviews establish the foundation of academic inquires. However, in the planning field, we lack rigorous systematic reviews. In this article, through a systematic search on the methodology of literature review, we categorize a typology of literature reviews, discuss steps in conducting a systematic literature review, and provide suggestions on how to enhance rigor in literature reviews in planning education and research.
Keywords: literature review, methodology, synthesis, typology
Title: Bridge network maintenance prioritization under budget constraint
Authors: Zhang, W. and N. Wang. (2017)
Journal: Structural Safety
This study develops a decision model to assist bridge authorities in determining a preferred maintenance prioritization schedule for a degraded bridge network in a community that optimizes the performance of transportation systems within budgetary constraints at a regional scale. The study utilizes network analysis methods, structural reliability principles and meta-heuristic optimization algorithms to integrate individual descriptive parameters such as bridge capacity rating, condition rating, traffic demand, and location of the bridge, into global objective functions that define the overall network performance and maintenance cost. The performance of the network is measured in terms of travel time between all possible origin-destination (O-D) pairs. In addition to the global budgetary constraint, the optimization is also conditioned on local constraints imposed on traffic flow by insufficient load carrying capacity of deficient bridges. Uncertainties in traffic demands, vehicle weights and maintenance costs are also considered in the problem formulation. Two project priority indices are introduced – the static priority index (SPI), defined as a function of the difference in network travel time between block running (with reduced load carrying capacity before repair) and smooth running (design-level load carrying capacity after repair) of a bridge, and the dynamic priority index (DPI) defined as the likelihood of a bridge being selected for repair when the budget is fixed and the uncertainties governing the performance of the transportation network are considered. Finally, this decision model is illustrated with a hypothetical network with 160 bridges.
Keywords: Transportation network, Travel time, Optimal maintenance scheduling, Prioritization, Optimization
Title: Probabilistic Prediction of Postdisaster Functionality Loss of Community Building Inventories Considering Utility Disruptions
Authors: Zhang, W., P. Lin, X. Xue, N. Wang, and C.D. Nicholson. (2017)
Journal: ASCE Journal of Structural Engineering
This study proposes a framework for the probabilistic prediction of building portfolio functionality loss (BPFL) in a community following an earthquake hazard. Building functionality is jointly affected by both the structural integrity of the building itself and the avail- ability of critical utilities. To this end, the framework incorporates three analyses for a given earthquake scenario: (1) evaluation of the spatial distribution of physical damages to both buildings and utility infrastructure; (2) computation of utility disruptions deriving from the cascading failures occurring in interdependent utility networks; and (3) by integrating the results from the first two analyses, making a probabilistic prediction of the postevent functionality loss of building portfolios at the community scale. The framework couples the functionality analyses of physical systems of distinct topologies and hazard response characteristics in a consistent spatial scale, providing a rich array of information for community hazard mitigation and resilience planning. An implementation of the BPFL framework is illustrated using the residential building portfolio in Shelby County, Tennessee, subjected to an earthquake hazard.
Keywords: Community resilience, Building functionality loss, Physical infrastructure, Interdependent utility networks Uncertainty modeling, Earthquake hazard
Title: OpenSeesPy: Python library for the OpenSees finite element framework
Authors: Zhu, M., McKenna, F., and Scott, M.H. (2017)
Journal: SoftwareX
OpenSees, an open source finite element software framework, has been used broadly in the earthquake engineering community for simulating the seismic response of structural and geotechnical systems. The framework allows users to perform finite element analysis with a scripting language and for developers to create both serial and parallel finite element computer applications as interpreters. For the last 15 years, Tcl has been the primary scripting language to which the model building and analysis modules of OpenSees are linked. To provide users with different scripting language options, particularly Python, the OpenSees interpreter interface was refactored to provide multi-interpreter capabilities. This refactoring, resulting in the creation of OpenSeesPy as a Python module, is accomplished through an abstract interface for interpreter calls with concrete implementations for different scripting languages. Through this approach, users are able to develop applications that utilize the unique features of several scripting languages while taking advantage of advanced finite element analysis models and algorithms.
Keywords: Interpreter, Scripting language, Structural analysis, Finite element analysis
Title: Probabilistic seismic demand assessment accounting for finite element model class uncertainty: Application to a code-designed URM infilled reinforced concrete frame building
Authors: Alam, M.S. and A.R. Barbosa. (2018)
Journal: Earthquake Engineering & Structural Dynamics
Reliable and robust probabilistic assessment of structures requires explicit consideration of all relevant sources of uncertainty, both aleatory and epistemic. This paper proposes a formulation to incorporate model class uncertainty in probabilistic seismic demand assessment (PSDA) of structures, where model class uncertainty relates to the use of different structural analysis models used to predict the physical response of structural systems. The application of the proposed formulation is illustrated through the assessment of a recent code-designed reinforced concrete (RC) frame building with unreinforced masonry (URM) infills, which is a prevalent form of construction worldwide. The model class uncertainty analyzed in this paper is related to the potential selection of one of three state-of-the-art masonry infill strut models. In the application example, nonlinear static pushover (NSP) analyses and tornado sensitivity analyses are performed to identify the important parameters of infill strut models affecting the seismic response of the infilled RC frame. A hybrid stripe analysis (HSA) approach is adopted to perform nonlinear response history analyses (NRHAs) of the example RC frame. To account for relevant sources of uncertainty, latin hypercube sampling (LHS) is used to quantify the minimum number of realizations of model parameters necessary to achieve convergence of the coefficient of variation (COV) of the engineering response parameters assessed. Results of the NRHAs indicate that incorporating model class uncertainty significantly affects the estimation of uncertainties of the drift hazard demand.
Keywords: drift hazard, epistemic uncertainty, hybrid stripe analysis, latin hypercube, model bias, model class uncertainty, RC frame, URM infill
Title: Hindcasting Community Level Damage to the Interdependent Buildings and Electric Power Network after the Joplin, Missouri, Tornado
Authors: Attary, N., J.W. van de Lindt, H. Mahmoud and S. Smith. (2018)
Journal: ASCE Natural Hazards Review
Tornados are common natural hazards that occur in the United States and result in social and economic loss. Resiliency of communities prone to tornadoes can be enhanced through the use of risk-informed decision-making tools. These tools can provide com- munity decision-makers with key information, thereby allowing them the ability to consider an array of mitigation and/or recovery strategies of relevant sectors in a community, including physical infrastructure, social and economic sectors. This study focuses on the community of Joplin, Missouri, which was struck by an EF-5 tornado on May 22, 2011. This tornado was the costliest and deadliest single tornado in the United States in the last 50 years. Initially, the damage caused by the tornado to the Electric Power Network (EPN) of the city is assessed by using a detailed topological data set obtained from the electric power company, combined with a spatial wind speed model and component fragilities. Many factors including the type of the electric poles, age, city growth rate, and so forth, were considered in this assessment. The results were compared with the damage reported from field studies following the event. Using the predicted damages to the poles, probabilities of power loss for each individual building in the city were calculated. A weighted cellular automata (CA) technique was used to estimate the service area of substations and the path that the electric power must travel to arrive at demand nodes. In addition, the effects of damage to the electric substations and transmission lines were considered. The results were compared with power loss reported by home and business owners to the electric power company. Combining the power loss probabilities with the probabilities of damage to build- ings in Geographic Information Systems (GIS) format, combined EPN-building probabilities of damage are presented. Such information can be used by decision makers for community resilience planning, and improvement.
Keywords: Electric power network, Joplin tornado, Cellular automata, Community damage assessment, Power loss
Title: Hindcasting Community Level Building Damage for the 2011 Joplin EF5 Tornado
Authors: Attary, N., J.W. van de Lindt, H. Mahmoud, S. Smith, C.M. Navarro, Y.W. Kim, and J.S. Lee. (2018)
Journal: Natural Hazards
Resiliency of communities prone to natural hazards can be enhanced through the use of risk-informed decision-making tools. These tools can provide community decision makers key information, thereby providing them the ability to consider an array of mitigation and/or recovery strategies. The Center for Risk-Based Community Resilience Planning, headquartered at Colorado State University in Fort Collins, Colorado, developed an Interdependent Networked Community Resilience (IN-CORE) computational environment. The purpose of developing this computational environment is to build a decision-support system, for professional risk planners and emergency responders, but even more focused on allowing researchers to explore community resilience science. The eventual goal was being to integrate a broad range of scientific, engineering and observational data to produce a detailed assessment of the potential impact of natural and man-made hazards for risk mitigation, planning and recovery purposes. The developing computational environment will be capable of simulating the effects from different natural hazards on the physical and socioeconomic sectors of a community, accounting for interdependencies between the sectors. However, in order to validate this computational tool, hindcasting of a real event was deemed necessary. Therefore, in this study, the community of Joplin, Missouri in the USA, which was hit by an EF-5 tornado on May 22, 2011, is modeled in the IN-CORE v1.0 computational environment. An explanation of the algorithm used within IN-CORE is also provided. This tornado was the costliest and deadliest single tornado in the USA in the last half century. Using IN-CORE, by uploading a detailed topological dataset of the community and the estimated tornado path combined with recently developed physics-based tornado fragilities, the damage caused by the tornado to all buildings in the city of Joplin was estimated. The results were compared with the damage reported from field studies following the event. This damage assessment was done using three hypothetical idealized tornado scenarios, and results show very good correlation with observed damage which will provide useful information to decision makers for community resilience planning.
Keywords: Joplin tornado, Community damage assessment, Tornado fragilities, Resolution
Title: A multidisciplinary definition and evaluation of resilience: the role of social justice in defining resilience
Authors: Doorn, N., P. Gardoni and C. Murphy. (2018)
Journal: Sustainable and Resilient Infrastructure
This paper aims to explore how insights from the philosophical and social science literature can be incorporated into the definition of resilient infrastructure so that considerations of social justice can be accounted for and addressed more adequately. Building on the view that engineering ultimately aims to promote societal well-being, this paper argues that human well-being depends on (1) the resilience of the physical infrastructure and (2) the socioeconomic context, both of which in turn affect (i) how the impact and recovery of the physical infrastructure translates into societal impact and recovery and (ii) the ability of individuals to recover/adapt independently from the recovery of the physical infrastructure. The paper suggests that a capability approach may be a suitable framework for providing content to the formal concept of resilience as a capability approach is especially suitable for expressing non-tangible damage that might be caused by natural hazards and disasters.
Keywords: Social justice, capability approach, well-being, critical infrastructures, resilience
Title: Social Vulnerability and Participation in Disaster Recovery Decisions: Public Housing in Galveston After Hurricane Ike
Authors: Hamideh, S. and J. Rongerude. (2018)
Journal: Natural Hazards
In September 2008, Hurricane Ike caused massive damages to Galveston Island’s residential structures including four public housing developments. These developments were located in neighborhoods with some of the lowest incomes and highest percentages of people of color on the Island. Four months later, the Galveston Housing Authority (GHA) decided to demolish all four developments consisting of 569 housing units due to the damages to the buildings. Today, despite federal regulations requiring reconstruction, court orders mandating replacement of the demolished units, and available funding, only 142 low-income apartments have been rebuilt. We used the social vulnerability framework to understand these outcomes through the ability of groups to shape post-disaster recovery decisions. This paper argues that one of the overlooked characteristics of social vulnerability is a diminished ability to participate in post-disaster decision-making. We found that social vulnerability limited participation through three distinct mechanisms: the physical displacement of public housing residents, the stigmatization of public housing, and the reduction of residents to housing units in the debates. There were few local advocates arguing for the preservation of public housing units and even fewer remaining residents to speak up for themselves in the face of strong local resistance to the reconstruction of public housing units or the return of public housing residents. The void of a strong and authentic local pro-public housing perspective in Galveston provided an opening for various local campaigns to claim that their desired plan benefited the poor. The disaster recovery became an opportunity to remove or reduce public housing units and therefore public housing residents. Our findings show the dynamic features of vulnerability. While static factors of vulnerability can limit access to resources for recovery, dynamic processes of social marginalization and exclusion limit the voices of socially vulnerable groups in recovery decisions and exacerbate marginalization.
Keywords: Public housing, Social vulnerability, Participation, Recovery decisions Hurricane Ike, Galveston
Title: Housing Recovery after Disasters: Primary versus Seasonal and Vacation Housing Markets in Coastal Communities
Authors: Hamideh, S., W.G. Peacock, and S. Van Zandt. (2018)
Journal: Natural Hazards Review
Recovery of seasonal housing after disasters is driven by different types of decisions and resource streams than those of year- round homes. Given the importance of seasonal rentals in the economies of coastal and particularly island communities, understanding the levels and recovery trajectories of seasonal housing may inform overall recovery expectations. The authors report findings from an empirical study of impact and recovery trajectories for owner-occupied and rental single-family housing in housing submarket areas in Galveston, Texas following Hurricane Ike using random-effects panel models to predict the parcel-level values over an eight-year period. Divergent impact and recovery trajectories and processes are found when comparing housing in residential markets with those in dynamic versus more languid vacation housing markets. Damage, tenure, minority population, and income all have significant effects on trajectories with varying directions and magnitudes across submarkets. These differences in the mechanisms of submarkets and vulnerability in recovery trajectories of coastal communities highlight the importance of mapping the influential factors in each area to target mitigation and recovery assistance effectively.
Keywords: Disaster; Housing recovery; Coastal; Vacation submarket
Title: A framework for estimating immediate interdependent functionality reduction of a steel hospital following a seismic event
Authors: Hassan, E. and H. Mahmoud. (2018)
Journal: Engineering Structures
Functionality of an infrastructure is its ability to provide its intended services. Maintaining an acceptable level of infrastructure functionality, particularly for critical infrastructure, following an extreme event is vital for effective community recovery. Estimating functionality depends on proper quantification of losses, which requires accurate assessment of infrastructure damage. The damage is presented in the form of fragility functions that are generally developed using nonlinear finite element analysis. To date, no study has been conducted to assess the effect of modeling approach on seismic fragilities of an infrastructure, the associated losses, and functionality reduction. In addition, existing frameworks for estimating functionality of critical infrastructure, such as a hospital, following an extreme event have not considered the interdependent relationship between a hospital and other lifelines. In this study, a new framework for evaluating immediate functionality of a hospital following an earthquake is presented. The functionality is estimated based on hospital losses that result from its sustained damage as well as damage to other lifelines on which the hospital relies. In addition, the effects of modeling resolution on the calculated fragilities, the estimated direct losses, and the associated functionality are evaluated. The hospital models vary from simplified 2-D with idealized boundary conditions to more comprehensive3-D models that account for soil-structure interaction. The analysis show that using simplified 2-D models that ignore soil-structure interaction could lead to non-conservative results. On the contrary, using more refined 3-Dmodels could provide accurate estimation of the behavior, and subsequently better assessment of losses and functionality.
Keywords: Hospital, Steel frame, 3-D modeling, Soil-structure interaction, Fragility, Direct losses, Immediate functionality, Lifeline interdependence
Title: Modeling the Damage and Recovery of Interdependent Civil Infrastructure Network Using Dynamic Integrated Network Model
Authors: He, X. and E.J. Cha. (2018)
Journal: Sustainable and Resilient Infrastructure
In a modern society, civil infrastructure facilities in different systems depend upon each other for product input and/or information sharing. Thus, understanding such dependencies and properly modeling them is essential to assess the performance of the civil infrastructure systems during and following a disruptive event, which lays the foundation of assessing the community resilience. This paper introduces the Dynamic Integrated Network model which is developed to assess the damage and recovery of the network of all considered systems following a disaster by considering the facility-level dependencies. A hypothetical study region consisting of electric power, potable water and cellular systems under a scenario hurricane is used to demonstrate the proposed model. A comparative study is performed with the case when inter-system dependency is ignored. This study confirms the importance of incorporating the inter-system dependencies to improve the estimation on the recovery process.
Keywords: Civil infrastructure, dependency, Dynamic Integrated Network, Operability, Recovery
Title: Modeling the damage and recovery of interdependent critical infrastructure systems from natural hazards
Authors: He, X. and E.J. Cha. (2018)
Journal: Reliability Engineering & System Safety
Understanding the impact of disasters to civil infrastructure network will guide strategic pre-disaster hazard mitigation and post-disaster recovery planning of a community. The facilities in civil infrastructure network depend on each other to exchange product, information or services. When disaster happens, these dependencies would aggravate the initial damage and lead to cascading failures. Thus, understanding the dependencies among infrastructure facilities is essential in modeling the damage and recovery of a community under disruptive events. This study builds upon the Dynamic Inoperability Input–output Model to assess the recovery of the civil infrastructure facilities by considering the facility-level dependencies. The recovery of the integrated network was assessed utilizing the characteristic parameters from graph theory. This methodology was demonstrated with a hypothetical infrastructure network, consisting of power, water and telecommunication systems under a hurricane. The sensitivity of the network recovery to the dependency measures was investigated, which showed that the recovery time is sensitive to the level of dependency between different systems. The proposed methodology was compared with a conventional model with system-level interdependencies and showed that considering facility-level dependencies would yield more refined result. The model was then applied to simulate the power system restoration of Galveston City, Texas under Hurricane Ike.
Keywords: Civil infrastructures, Dependency, Dynamic Inoperability Input–output Model, Graph theory, Hurricane winds, Recovery
Title: Uncertainty, learning, and local opposition to hydraulic fracturing
Authors: Hess, Joshua, D. T. Manning, T. Iverson and H. Cutler. (2018)
Journal: Resource and Energy Economics
New extraction technologies, including hydraulic fracturing(fracking), have increased fossil fuel reserves in the United States. Despite local economic benefits, many jurisdictions have adopted bans on fracking. We develop a dynamic learning model parameterized with a computable general equilibrium(CGE)model to quantify the associated quasi-option value(QOV), and to explore if uncertainty about environmental damages with the potential to learn can rationalize such bans. The model is calibrated to a representative municipality in Colorado, the site of several fracking bans. With plausible damages, we find that the QOV increases the incentive to delay drilling within a range of energy prices. The results suggest that improving the ability to learn about fracking impacts could increase the prevalence of bans in the short run and lead to better policy making over time. Incorporating CGE output in to a dynamic learning framework permits calculation of the locality-wide QOV associated with arrange of policies.
Keywords: Hydraulic fracturing, Quasi-Option value, Stochastic dynamic program, Computable general equilibrium model, Learning
Title: State-dependent stochastic models: A general stochastic framework for modeling deteriorating engineering systems considering multiple deterioration processes and their interactions
Authors: Jia G, and P. Gardoni. (2018)
Journal: Structural Safety
For performance analysis of deteriorating engineering systems, it is critical to model and incorporate the various deterioration processes and associated uncertainties. This paper proposes state-dependent stochastic models (SDSMs) for modeling the impact of deterioration on the performance of engineering systems. Within the stochastic framework, the change of the system state variables due to different deterioration processes and their interaction is modeled explicitly. As a candidate model to be used in the framework, a new general age and state dependent stochastic model for gradual deterioration is pro-posed, and its calibration based on data is also discussed. Once the time-variant system state variables are modeled, proper capacity and demand models that take them as inputs can be adopted to fully cap-ture the impact of deterioration processes on the capacity, demand, and other system performances. The proposed framework is first demonstrated through a simple example, and then is used to model the deterioration of an example reinforced concrete (RC) bridge considering deterioration caused by both corrosion and earthquake including their interaction. The results show the importance of modeling the interaction between different deterioration processes, and also verify the advantages of the proposed framework.
Keywords: Stochastic models, Deterioration modeling, Multiple deterioration processes, Reinforced concrete bridges, Seismic damage, Corrosion
Title: Simulation-based approach for estimation of the stochastic performances of deteriorating engineering systems
Authors: Jia G, and P. Gardoni. (2018)
Journal: Probabilistic Engineering Mechanics
Engineering systems suffer from deterioration over time due to either aging, regular operation, or extreme loading/environmental conditions. It is critical to model and incorporate deteriorations in the stochastic performance assessment of deteriorating engineering systems. However, deterioration modeling usually entails complex models and large number of uncertainties, where closed-form solutions are not available for estimation of the stochastic performance measures. Some of the traditional approaches face challenges in handling nonlinear models and large number of uncertainties. This paper discusses the use of general simulation-based approach for estimation of the stochastic performance of deteriorating engineering systems. The simulation-based approach allows consideration of various uncertainties associated with the external conditions, deterioration models, performance valuation models, and puts no constraints on the complexity of the adopted models. Simulation-based estimation of performance measures such as instantaneous failure probability, number of shocks to failure, and failure time are established. Also, simulation-based evaluation of various life-cycle performance quantities is discussed with a focus on simulating samples from the probability distributions needed for this evaluation. As key steps in the approach and also the novel contributions, the paper develops explicit simulation steps and equations for the simulation of the stochastic load occurrence, realizations of deterioration processes considering both gradual and shock deteriorations with state-dependent deterioration models, as well as samples for estimating life-cycle performance quantities. Adoption of advanced simulation techniques (e.g., Importance Sampling) is also discussed to further improve the estimation efficiency and reduce the computational effort. The developed simulation-based approach is applied to the stochastic performance evaluation of a reinforced concrete (RC) bridge considering deterioration caused by both earthquakes and chloride-induced corrosion. The computational performance is discussed in detail within the context of the example.
Keywords: Simulation-based approach, Stochastic performance, Failure probability, Life-cycle performances, Deterioration, Seismic damage, Corrosion
Title: Nonlinear Modeling of Wood-Frame Shear Wall Systems for Performance-Based Earthquake Engineering: Recommendations for the ASCE 41 Standard
Authors: Koliou, M., J.W. van de Lindt, R.O. Hamburger. (2018)
Journal: ASCE Journal of Structural Engineering
Wood shear wall systems are the primary elements of seismic force-resisting system (SFRS) in virtually all light-frame wood buildings. Wood-frame buildings are unique because their nonstructural wall finishes, such as gypsum wallboard and stucco, provide significant strength and stiffness relative to that of the intended SFRS. Given the fact that nonstructural wall finishes can consist of multiple layered materials, it is essential to understand and characterize their behavior. The development of accurate and robust numerical models to capture the inelastic behavior of individual shear wall systems and buildings comprised of these wall systems is a critical step when performing nonlinear analyses for either design, evaluation, or upgrade of existing buildings using standards such as ASCE 41-13 [(ASCE 2013). ASCE 41-13: Seismic evaluation and retrofit of existing buildings]. In general, existing modeling approaches do not account for the implementation of residual strength and displacement, which have been observed for light-frame wood buildings during shake-table tests. Furthermore, nonlinear representation of elements in the ASCE 41 standard considers only cyclic envelopes to define the nonlinear response of wood shear wall systems and not full hysteretic properties. To address these challenges, this study was divided into three main parts. The first part focused on the development of an excessive synthesis of wall assembly tests incorporating different wood sheathing materials and material combinations, and the evaluation of their force-displacement response. The second part introduced a new envelope curve proposed for modeling wood-frame wall systems with the parameters of this curve identified for the different material combinations included in the synthesis of Step 1. Finally, the proposed backbone curve was implemented in a case study of a multifamily wood frame building subjected to seismic excitation. Incremental dynamic analyses were conducted considering both the proposed envelope curve and the ASCE 41 modeling recommendations, and the response of the building structure was evaluated for three different performance levels (immediate occupancy, life safety, and collapse prevention) through fragility analysis. The main objective of this study was to introduce a beneficial wall-system level modeling tool for nonlinear analysis of light-frame wood buildings as specified in codes and standards in the United States.
Keywords: Performance-based earthquake engineering; Wood shear walls; Nonlinear time history analysis; Collapse capacity; Fragility curves; Backbone curve; ASCE 41; System level response
Title: Unraveling the Complexity of Wildland Urban Interface Fires
Authors: Mahmoud, H. and A. Chulahwat. (2018)
Journal: Scientific Reports
Recent wildland urban interface fires have demonstrated the unrelenting destructive nature of these events and have called for an urgent need to address the problem. The Wildfire paradox reinforces the ideology that forest fires are inevitable and are actually beneficial; therefore focus should to be shifted towards minimizing potential losses to communities. This requires the development of vulnerability-based frameworks that can be used to provide holistic understanding of risk. In this study, we devise a probabilistic approach for quantifying community vulnerability to wildfires by applying concepts of graph theory. A directed graph for community in question is developed to model wildfire inside a community by incorporating different fire propagation modes. The model accounts for relevant community-specific characteristics including wind conditions, community layout, individual structural features, and the surrounding wildland vegetation. We calibrate the framework to study the infamous 1991 Oakland fire in an attempt to unravel the complexity of community fires. We use traditional centrality measures to identify critical behavior patterns and to evaluate the effect of fire mitigation strategies. Unlike current practice, the results are shown to be community-specific with substantial dependency of risk on meteorological conditions, environmental factors, and community characteristics and layout.
Title: Wind Performance Enhancement Strategies for Woodframe Buildings
Authors: Masoomi, H., M. R. Ameri, and J.W. van de Lindt. (2018)
Journal: ASCE Journal of Performance of Constructed Facilities
Extreme winds such as tornadoes and hurricanes are relatively common natural hazards in the United States and can result in fatalities as well as damaging physical and socioeconomic infrastructure. Buildings are a critical sector within the built environment of a community and studying their performance under natural hazards is a major step for the risk and resilience assessment of a community. More than 80% of the total building stock in the United States and more than 90% of the residential buildings in North America are wood-frame construction; a construction type that is vulnerable to wind damage because they are light and typically are not engineered, only prescriptive in their design. Performance enhancement strategies for wood-frame residential buildings were investigated in this study by exploring combinations of roof coverings, roof sheathing nailing patterns, and roof-to-wall connection types. In this regard, a total of nine construction product combinations were considered. Further, recent changes to the wind standards were also explored. Specifically, the damage fragilities of five wood-frame building archetypes are considered for four damage states defined based on the performance of the building envelope, including roof coverings, doors and windows, roof sheathing, and roof-to-wall connections. The fragility curves are explained at the component level and then the building level for one archetype as an example, and the building fragility parameters are provided for all archetypes and for all construction product combinations. Comparison between fragilities developed using the last two versions of the wind standards are also presented. Then, an existing approach that amplifies the wind pressures in the wind standards to represent a tornado load is also com- pared. The fragility curves provided in this study can be used to represent residential buildings within a community for risk or resilience assessment/mitigation under hurricane or tornado loading.
Keywords: Damage fragility, Performance assessment, Wood-frame buildings, Tornado, Hurricane, Risk mitigation, Residential buildings
Title: Combined Wind-Wave-Surge Hurricane-Induced Damage Prediction for Buildings
Authors: Masoomi, H. and J.W. van de Lindt, M.R. Ameri, T. Q. Do, and B. M. Webb. (2018)
Journal: ASCE Journal of Structural Engineering
Coastal structures are subjected to multihazard events such as hurricanes which consist of hurricane-induced surge and waves as well as winds. Hurricanes are a common natural hazard in the United States and cause considerable damage every year, with resulting annualized losses in the United States in the tens of billions of dollars. Although improvements in construction practices have been notable over time for individual hazards, there is still a dearth of risk and damage prediction methods in the area of multiple hazards that are based on principles of mechanics. In this study, a methodology to develop multihazard damage fragilities is summarized and illustrated for a wood- frame residential-building archetype subjected to hurricane winds, storm surge, and waves. The National Flood Insurance Program (NFIP) requires new buildings along the US coastline to be constructed with the first finished floor set at an elevation that exceeds a minimum necessary elevation. Therefore, two different elevations are considered for the lowest horizontal structural member of the archetype to also examine its effect on damage fragilities. The developed multihazard fragilities are used to calculate the time-dependent probability of each damage state at a given location over the timeframe of an event, i.e., hurricane. In this regard, the spatial and temporal data of wind speeds, flood depths, and significant wave heights for Hurricane Ike are simulated by the ADCIRC + SWAN model (a tightly coupled version of the ADvanced CIRCulation model and the Simulating WAves Nearshore model for simulating the propagation of storm surge and waves from deep water to the coastal region). The performance of nonelevated and elevated archetypes is examined at different locations in southeast Texas for Hurricane Ike and a scenario of damage states predicted for this area for the elevated archetype.
Keywords: Multihazard, Fragility, Advanced circulation model (ADCIRC), Simulating waves nearshore model (SWAN), Hurricane Ike, Coastal area.
Title: Minimal Building Fragility Portfolio for Damage Assessment of Communities Subjected to Tornadoes
Authors: Memari, M., N. Attary, H. Masoomi, H. Mahmoud, J.W. van de Lindt, S.F. Pilkington, M. Ameri. (2018)
Journal: ASCE Journal of Structural Engineering 10.1061/(ASCE)ST.1943-17 541X.0002047
Tornadoes are considered a low-probability high-consequence event that can cause significant damage to community infrastruc ture, resulting in injuries and fatalities and ultimately creating long-term socioeconomic losses. Community resilience requires not only that the performance level of individual facilities be modeled and understood, but also their synthesis in space and time. Fragilities are conditional statistical distributions that provide the probability of exceeding analyst-defined performance levels as a function of hazard (or loading) intensity. Fragilities are becoming a core component in community resilience studies and enable the analyst to model performance of individual components or a cluster of the infrastructure, thereby supporting risk-informed decision making at the community level. In this paper, tornado fragilities for a portfolio of nonresidential buildings are developed. These fragilities, combined with several existing tornado building fragilities from the literature, are proposed to represent a first comprehensive minimum size portfolio of tornado building fragilities needed to model a community. For illustration, they are then used in the Centerville virtual community to perform community-level building damage assessment. This minimal-level portfolio of building fragilities lays the foundation for post-tornado recovery and resilience studies of a community, which eventually requires inclusion of all physical and nonphysical infrastructure.
Keywords: Building portfolio, Tornado, Spatial building damage, Tornado fragility, Centerville virtual community, Community resilience.
Title: Numerical modeling of non-breaking, impulsive breaking, and broken wave interaction with elevated coastal structures: Laboratory validation and inter-model comparison
Authors: Park, H., T. Do, T. Tomiczek, D.T. Cox, and J.W. van de Lindt. (2018)
Journal: Ocean Engineering
Quantitative CFD model validation and inter-model comparisons between IHFOAM and ANSYS-FLUENT were performed for pressures and forces on an elevated structure using a 1:10 physical model. Non-breaking, impulsive breaking, and broken wave conditions at the structure's location were simulated in IHFOAM and FLUENT. The calculated time series of water surface elevation and horizontal and vertical pressures and forces were compared with the measured data. We introduced the impulse of residual to quantify the variation of the force and pressure time series. Results indicated that the numerical models performed differently depending on the wave conditions, even for the same initial set up. Non-breaking wave simulations showed the best agreement with experimental data for both models, while broken wave trials showed the largest deviations. Bottom pressures and vertical forces were less sensitive to wave breaking conditions. Results indicate that future benchmarking tests for an elevated structure must consider both horizontal and vertical forces due to various wave breaking conditions. The accuracy of simulated wave shoaling and breaking processes played a key role in precisely calculating the forces and pressures on the structure, and it was difficult for the CFD models to simulate the exact wave breaking conditions as the measurements.
Keywords: Experiment, IHFOAM, ANSYS FLUENT, Validation, Force, Pressure
Title: Resilience modeling of traffic network in post-earthquake emergency medical response considering interactions between infrastructures, people and hazard
Authors: Wu, Y. and S. Chen. (2018)
Journal: Journal of Sustainable and Resilient Infrastructure
Timely rescue of injured people by emergency medical services (EMS) is essential for disrupted traffic networks due to the failures of transportation infrastructure following major hazards. Rational resilience performance indicators in terms of EMS cannot only help implementing an optimized post-disaster medical response plan, but also identify the most cost-effective pre-disaster preventive measures. A framework to assess the resilience performance of a typical traffic network in terms of post-earthquake EMS is developed by considering the interactions between building infrastructures, injured people, vulnerable medical centers, EMS vehicles, disrupted traffic network, and natural hazards. Two resilience performance indicators are introduced characterizing the relative importance of different links and overall EMS resilience for the whole network. A virtual community is selected to demonstrate the proposed framework, which is followed by a parametric study of the earthquake magnitude, bridge types, location and number of medical centers, and optimal location for a new medical center.
Keywords: Emergency medical response, traffic network, disruption, earthquake, resilience
Title: Full-response prediction of the coupled long-span bridge and traffic system under spatially varying seismic excitations
Authors: Zhou, Y. and S. Chen. (2018)
Journal: ASCE Journal of Bridge Engineering
A long-span bridge supports a large number of vehicles, which are usually present when an earthquake strikes the bridge site due to the low predictability of earthquake events. Existing seismic analyses of long-span bridges have failed to characterize the comprehensive coupling effects among the bridge structure, vehicles, and spatially varying seismic excitations. A new full-response prediction methodology for the coupled bridge–traffic interaction system under spatially varying earthquake excitations was developed by capturing the interaction effects not only between the bridge and moving vehicles, but also between the earthquake excitations and the coupled bridge–traffic system. Different from most existing bridge seismic analyses, in which only traditional earthquake loads in terms of inertial forces are applied on the bridge structure, the new formulation also incorporated the coupled earthquake forces on both the bridge and vehicles, which were expressed as functions of the bridge–traffic coupling matrices and earthquake displacement inputs. The proposed methodology was numerically demon- strated on a prototype long-span bridge and traffic system under spatially varying earthquake excitations. The full responses of the bridge and vehicles were predicted when the bridge–traffic system was subjected to earthquake excitations. Numerical results suggest that the coupled earthquake force as derived in the present study has notable influence on the dynamic performance of the bridge and vehicles under seismic excitations.
Keywords: Seismic response, Long-span bridges, Vehicles, Stochastic traffic, Earthquake, Dynamic interaction, Resilience
Title: Investigation of the Live-Load Effects on Long-Span Bridges under Traffic Flows
Authors: Zhou, Y. and S. Chen. (2018)
Journal: ASCE Journal of Bridge Engineering
Different from short-span girder bridges, long-span bridges support a large amount of traffic, which significantly influences the dynamic performance of the bridge. The design live load on long-span bridges has seldom been investigated to take into account the dynamic effects from multiple vehicles in traffic flow. The current AASHTO LRFD specification was primarily developed for and calibrated from bridges with spans of 61.0 m (200 ft) or less. Therefore, it is unknown whether it is risky or conservative to use the same design live load from AASHTO on long-span bridges with spans longer than 100 m. Taking advantage of the advanced simulation methodology on the coupled bridge-traffic system developed recently, the live-load effects on a prototype long-span bridge from stochastic traffic flow were comprehensively studied, including the extreme dynamic response and the dynamic amplification factors for different bridge components. To evaluate the applicability of the design live-load in the current AASHTO specification on long-span bridges, the load effects on the prototype long-span bridge were numerically assessed and were compared with the corresponding response envelopes of the bridge under stochastic traffic flow. It was found that the design live load from AASHTO may be unsafe for use as the live load for the design of the bridge girder, pylon, and stay cables for long-span bridges.
Keywords: Long-span bridges, Design live load, Traffic flow, Dynamic effects, Dynamic amplification factor(DAF)
Title: Seismic performance and Recovery Modeling of Natural Gas Networks at the Community Level using Building Demand
Authors: Ameri, M.R. and J.W. van de Lindt. (2019)
Journal: Journal of Performance of Constructed Facilities
Earthquakes can substantially disrupt the operation of critical lifelines in a community, particularly water, gas, and other below-ground infrastructure. The damage that occurs to lifelines in a community from an earthquake can, in turn, have a substantial impact, resulting in social and economic disruption. Furthermore, the duration of the loss in functionality of lifelines is a key factor in the economic disruption that results from an earthquake. In this study, a virtual community known as Centerville was subjected to earthquakes of varying intensity, each having the same assigned point source location, using a well-known attenuation model in order to examine the restoration of communities in the aftermath of an earthquake. The virtual community model being studied has the essential physical components that describe a community, but the focus of this paper is the natural gas network, which is composed of a processing plant, compressor stations, city gate stations, district regulating stations, and buried pipelines. Based on the level of damage that occurred to the network components and their connectivity (topology) throughout the community, the functionality of supplier nodes is assessed using Monte Carlo simulation, and functionality curves are presented for the community’s natural gas network. Notably, the effect of the industrial makeup of a community on its natural gas recovery following an earthquake, as well as the influence of replacing conventional steel pipes with high-density polyethylene (HDPE) ductile pipelines, is examined. As expected, the ability of the HDPE pipe to reduce the network recovery time is substantial and is quantifiable at the community level using the approach presented herein.
Keywords: Community resilience; Natural gas network; Functionality assessment; Community-level restoration
Title: Performance-Based Tsunami Engineering for Risk Assessment of Structures Subjected to Multi-Hazards: Tsunami following Earthquake
Authors: Attary N., van de Lindt J.W., Barbosa A.R., Cox D.T. and Unnikrishnan V.U. (2019)
Journal: Journal of Earthquake Engineering
Tsunamis are low-probability high-consequence events, usually caused by an earthquake in the ocean and can result in high casualty rates and billions of dollars in damage. Tsunamis can be divided into two main categories: near-field and far-field tsunamis, based on the location of their origin with respect to the site of interest. To perform risk assessment of communities subjected to tsunamis, the current approach would be to use empirical data from historical events, making the data site specific. Recently, researchers have developed approaches to estimate the risk of structures subjected to far-field earthquake generated tsunamis using a simulated tsunami force on a structure numerically. However, for near-field tsunamis, ground motions caused by the earthquake will reach the structure earlier than the tsunami, damaging the structure, which can substantially impair its structural performance in the following tsunami. The multi-hazard case of tsunami following earthquake is discussed herein and a physics-based approach to estimate the risk of structures subjected to them is presented. An illustrative example is presented to elaborate the methodology for a steel building. Successive nonlinear analyses are used to develop fragility functions based on joint earthquake-tsunami intensity measures (spectral acceleration-flow depth-flow velocity). These functions are used in combination with hazard analysis of a specific location to obtain loss estimates. Three different approaches were used for this process and the results showed that the use of the joint three intensity-measure fragilities is essential for the accuracy when estimating damage or structural loss and neglecting their interaction results in substantial errors.
Keywords: Multi-Hazard, Tsunami, Earthquake, Performance-Based Engineering, Loss Analysis, Monte Carlo Simulation, Risk Assessment
Title: Selection of Residential Building Design Requirements to Achieve Community Functionality Goals under Tornado Loading
Authors: Farokhnia, K., J.W. van de Lindt, and M. Koliou. (2019)
Journal: Practice Periodical on Structural Design and Construction
An essential aspect of community disaster recovery planning is understanding the recovery process and developing appropriate probability-based recovery simulation tools to account for interdependent systems of lifeline networks (i.e., water, electrical power, and transportation systems) with the building infrastructure. The objective of this study is to illustrate selection of residential design code changes that are needed to achieve the recovery goals of a virtual community. In the present illustration, the community goals are expressed in terms of functionality of the built environment. This paper focuses only on the electric power network and building clusters subjected to tornado loads. A single combination of design changes selected from three alternatives is demonstrated to achieve the functionality goals at key points in time during the recovery process.
Keywords: Community resilience, Tornado recovery, Interdependencies, Restoration; Buildings, Electrical power network.
Title: Integration of physical infrastructure and social systems in communities’ reliability and resilience analysis
Authors: Guidotti, R. P. Gardoni and N. Rosenheim. (2019)
Journal: Reliability Engineering & System Safety
This paper proposes probabilistic flow-based models for the capacity and demand of critical infrastructure considering different levels of resolution. The models are set in a probabilistic procedure that captures the impact of the damaging event on the infrastructure. The procedure predicts the reduction or loss of functionality of the infrastructure in terms of their ability to provide essential goods or services. In the aftermath of a damaging event, infrastructure change their capacities, due to the damage to the physical components, and they may not be able to satisfy pre-event demands. Furthermore, the post-event demands at the nodes of the infra-structure might change because of the human response (e.g., evacuation or relocation.) The probabilistic procedure presented in this paper integrates physical infrastructure and social systems to predict the change in demand on the infrastructure. As an example, the paper applies the proposed procedure to the modeling of the potable water network of Seaside, Oregon considering a seismic event as the damaging event. The paper shows that neglecting the interdependency between physical infrastructure and social systems may result in estimates of i) higher demands on the physical systems; ii) slower recovery; and iii) smaller impacts on society in terms of population dislocation.
Keywords: Physical infrastructure, Social systems, Capacity, Demand, Flow, Community resilience
Title: Simulation of Hurricane Wind Fields for Community Resilience Applications: A Data-Driven Approach Using Integrated Asymmetric Holland Models for Inner and Outer Core Regions
Authors: Guo, Y., and van de Lindt, J.W. (2019)
Journal: Journal of Structural Engineering
Accurate modeling of the damage caused by hurricanes making landfall to physical infrastructure relies on the accurate modeling of temporally and spatially varying wind fields. However, wind field measurements from past events only include the wind field data at discrete time points separated by hours. In community-scale modeling, a hurricane wind field of a desired strength for the purpose of resil- ience planning (including investigation of mitigation alternatives) may be needed for a community of interest that has not experienced such a prior event, thereby necessitating simulation of a hurricane wind field of a specified strength with an arbitrary landfall location. In this context, this paper proposes a novel data-driven simulation technique to simulate temporally and spatially varying hurricane wind fields for the purposes of hindcasting and synthetic scenario analysis based on integrated asymmetric Holland models. First, the backward Holland model (i.e., Lambert W function) is used to derive the time-varying model parameters from measurement data of historical events. Then the data- driven model parameters are adopted in the forward Holland model to simulate snapshots of missing times for historical events or realistic synthetic events with a synthetic track passing close to the community of interest (e.g., for the purpose of community resilience planning). To achieve high simulation accuracy, the wind fields for inner and outer core regions are modeled separately by two sets of asymmetric Holland models, whose parameters are estimated using two different branches of the Lambert W function and in the end are integrated to represent the entire wind field. In addition, the sudden change of the surface wind speed due to the roughness change from water to land is explicitly modeled using a speed conversion process. In this way, the proposed technique successfully overcomes two shortcomings of the existing Holland-type models, that is, poor representation of the wind field in the inner core region and the inability to model surface wind speed change due to roughness changes. The performance of the proposed data-driven simulation technique is illustrated in examples of simulations for both historical and synthetic hurricanes.
Keywords: Hurricane wind field simulation; Data-driven; Asymmetric wind field; Backward and forward Holland models; Inner and outer cores
Title: Traffic Performance Assessment Methodology of Degraded Roadway Links Following Hazards
Authors: Hou, G., S. Chen and Y. Han. (2019)
Journal: J. of Aerospace Engineering, ASCE
Post hazard traffic networks are often disrupted, not only because of direct impacts on transportation infrastructure but also because of indirect impacts originating from the interdependent nature of infrastructure systems and environments. These indirect impacts include roads blocked by debris from adjacent buildings, traffic accidents, or fallen trees or light poles. For all these scenarios with partially blocked roads and bridges following extreme events, traffic capacity and travel time are very different what they are with intact road infra- structures and, therefore, become hard to predict. A new simulation methodology of the traffic performance of partially blocked roadway and bridge links due to hazardous events is proposed in this paper. The methodology was based on improved microscopic-scale traffic flow simulation techniques that can be applied to degraded road/bridge links with various types of obstacles (different sizes, numbers, and distributions). Following validation with the published results of traffic congestion induced by a work zone, two typical partially blocked scenarios resulting from infrastructure damage and accidents were numerically analyzed to demonstrate the feasibility of the application of the methodology to the traffic performance prediction of disrupted roadways due to extreme events. Parametric studies, such as the impact of truck proportion, blockage configuration, and traffic control measures, were also conducted. It was found that the proposed framework can predict the traffic performance of degraded transportation systems due to various causes, which could contribute to a wide array of future studies, such as community resilience modeling, emergency response and evacuation planning, and so forth.
Keywords: Disrupted traffic; Cellular automaton; Traffic simulation; Partially blocked roadways; Hazardous events; Traffic performance; Resilience
Title: Framework of simulation-based vehicle safety performance assessment of highway system under hazardous driving conditions
Authors: Hou, G., S. Chen, and F. Chen. (2019)
Journal: Journal of Transportation Research Part C: Emerging Technologies
Vehicles are extremely vulnerable to single-vehicle accidents under some hazardous driving conditions (i.e. strong wind, icy or snowy road surface). An integrated framework is proposed to assess single-vehicle traffic safety performance of stochastic traffic flow under hazardous driving conditions. Different from most existing studies focusing on a single vehicle moving at a constant speed, for the first time, the proposed work evaluates individual vehicle safety performance based on the time-dependent simulation results of stochastic traffic flow, including instantaneous speeds and positions of each vehicle as a part of simulated traffic flow. Simultaneously, complex geometric and other environmental conditions of the highway system are also considered realistically, not only during the safety assessment process, but also in quantifying the wind loads applied on the vehicles. Finally, with the safety information of each individual vehicle, an overall safety performance index of the whole traffic flow on the highway system is further introduced, which serves as a potential traffic safety performance measure and resilience indicator of transportation infrastructure systems under various hazards. This study has potential applications to not only regular vehicles, but also advanced traffic management and control algorithms for connected and autonomous vehicles in hazardous driving environments.
Keywords: Vehicle safety, Accident, Cellular automaton, Hazardous driving conditions, Highway system
Title: Stochastic life-cycle analysis: renewal-theory life-cycle analysis with state-dependent deterioration stochastic models
Authors: Jia, G., and P. Gardoni. (2019)
Journal: Structure and Infrastructure Engineering
For the life-cycle analysis (LCA) of deteriorating engineering systems, it is critical to model and incorporate the various deterioration processes and associated uncertainties. This paper proposes a renewal-theory life-cycle analysis (RTLCA) with state-dependent stochastic models (SDSMs) that describe the deterioration processes. The SDSMs capture the multiple deterioration processes and their interactions through modelling the changes in the system state variables due to different deterioration processes. Then proper capacity and demand models that take the time-variant state variables as input are adopted to fully capture the impact of deterioration processes on the capacity, demand, and other time-variant performance indicators of the engineering system. The SDSMs are then integrated into RTLCA to efficiently evaluate various life-cycle performance quantities such as availability, operation cost and benefits of the engineering system. To implement the proposed formulation, a sampling-based approach is adopted to simulate samples from the relevant probability density functions (PDFs) to estimate the life-cycle performance quantities, while stochastic simulation-based approach is adopted to estimate the time-variant performance indicators needed to inform intervention activities. As an illustration, the proposed formulation is used to analyse the life-cycle performances of an example reinforced concrete bridge subject to deterioration due to corrosion and seismic loading.
Keywords: Stochastic models, life cycle costs, deterioration, corrosion, seismic effects, structural reliability, reinforced concrete bridges
Title: Decision tree based bridge restoration models for extreme event performance assessment of regional road networks
Authors: Kameshwar, S., S. Misra, and J. E. Padgett. (2019)
Journal: Structure and Infrastructure Engineering
Bridge restoration models are essential for assessing the functionality of bridges after extreme events, emergency response planning, and evaluating resilience and indirect losses. Most of the existing restoration models lack explicit evaluation of anticipated bridge functionality in terms of traffic restrictions on bridges, which is necessary for realistic road network modeling. Therefore, this paper proposes a decision tree based approach to determine potential traffic restrictions and their durations using empirical and expert opinion survey data on restrictions imposed on bridges after extreme events. The proposed methodology is applied in this paper to obtain seismic restoration models for bridges. Herein, three separate decision trees are developed to determine various traffic restrictions, anticipated for different levels of damage to bridge components, including bridge closure, lane closure, and speed/load restriction. Corresponding to each of the three traffic restriction decision trees, another decision tree is developed which determines the duration of the traffic restriction. The probabilistic seismic performance of a regional highway network in Memphis, Tennessee, is studied using the proposed decision trees. Additionally, HAZUS bridge restoration functions are also applied and the differences in the time evolving bridge level functionality estimates and their impacts on network performance are highlighted.
Keywords: Bridge restoration, decision tree, traffic restrictions, earthquakes, extreme events, road networks
Title: Probabilistic decision-support framework for community resilience: Incorporating multi-hazards, infrastructure interdependencies, and resilience goals in a Bayesian network.
Authors: Kameshwar, S., H. Park, S. Alam, K. Farokhnia, A. Barbosa, D. Cox, J.W. van de Lindt (2019)
Journal: Reliability Engineering and System Safety
A probabilistic decision support framework is developed in this study for community resilience planning under multiple hazards using performance goals based guidelines such as the Oregon Resilience Plan and the National Institute of Standards and Technology Community Resilience Planning Guide. Herein, resilience of community infrastructure systems is defined as the joint probability of achieving robustness and rapidity based performance goals, which is quantified using Bayesian networks. The framework assesses the effects of decision support options such as selection of hazards, resilience goals, and mitigation (ex-ante) and response (ex-post) strategies to identify measures that can improve infrastructure performance to meet community defined resilience goals. This framework is applied for resilience assessment of building, transportation, water, and electric power infrastructure systems in Seaside, Oregon, under combined earthquake ground shaking and tsunami inundation hazards corresponding to different return periods. Uncertainties in damage, restoration, and economic losses are explicitly considered and propagated in the framework using Monte Carlo simulation (MCS). The MCS results are then used to inform the Bayesian network, which evaluates the joint resilience of infrastructure systems in Seaside. Results highlight the impact of considering different performance goals, introduction of ex-ante and ex-post measures, and interdependencies between various infrastructure systems on infrastructure resilience.
Keywords: Bayesian networks, Community resilience, Decision support, Infrastructure, Performance goal, Resilience goals
Title: Development of Building Restoration Functions for use in Community Recovery Planning to Tornadoes
Authors: Koliou, M. and van de Lindt, J.W. (2019)
Journal: ASCE Natural Hazards Review
Post-disaster community scale recovery and resilience assessment have gained interest in the United States and around the world following natural and human-made disasters. Tornadoes are one of the most devastating natural disasters that occur in the United States every year with an annual average of over 1,200 causing an impactful number of deaths as well as economic losses. The post-disaster recovery planning and process of communities can be enhanced by the use of risk-informed decision making tools accounting for post-disaster vulnerability and restoration assessment in terms of repair time (functionality) and repair cost (economic losses). In this study, a methodology to probabilistically quantify building functionality through the development of functionality fragilities for use within broader community modeling is introduced. It is important when performing community resilience assessment studies to break down the components making up a community into their most fundamental components.  Thus, it is proposed to generate stand-alone functionality fragilities (e.g. for different building types) and thereby not limit the process for optimizing risk-informed decision making, which may include options such as changes in permitting time, or removal of construction constraints. The proposed functionality methodology is comprised of four steps while integrating concepts of performance based engineering, where functionality analyses are first performed for each major component in the building including both structural and non-structural components (sub-assembly level) and then the results are combined in the form of statistical distributions to quantify the building (system level) functionality. The methodology is illustrated for a suite of 19 building types ranging from residential, school and hospital representative of the building stock in the US communities needed to model a community that is heavily impacted by an extreme wind event (i.e., tornado).  The post-tornado building direct economic losses are also probabilistically assessed for the 19 building archetypes. Repair times (functionality) and repair cost distribution curves summarized in this study may be further used in risk-informed decision making for investigation of policy implications, the effect of retrofit programs, and other changes to building codes.
Keywords: Post-disaster recovery, Repair time and cost functions, Buildings, Natural hazards, Tornadoes, Functionality
Title: Seismic Fragility of Railway Bridge Classes: Methods, Models and Comparison with State-of-the-Art
Authors: Misra, S. and Padgett, J.E (2019)
Journal: ASCE Journal of Bridge Engineering
This study proposes an approach for developing seismic fragility models based on elastic net regularized logistic regression and applies it to two railway bridge classes typical to the central and southeastern United States (CSUS). Railway bridge class fragilities are not available in the literature despite recorded evidence of earthquake damage to railway bridges. The introduction of elastic net regularization helps in selecting the best set of predictor variables for fragility modeling even if they are mutually correlated. The proposed fragility models are compared to their corresponding highway bridge counterparts, given that current practice in regional risk assessment recommends adopting these as proxies for railway bridge fragility. The analysis reveals that multispan simply supported steel girder railway bridges, the most common bridge class, show lower fragility than their corresponding highway bridge counterparts. However, multispan simply supported steel through plate girder railway bridges, the other common bridge class, show comparatively higher seismic fragility. The proposed fragility models serve as key inputs in a broader framework of quantifying seismic resilience of railway networks, as well as providing a practical baseline for seismic loss assessment and retrofit prioritization.
Title: Time-Dependent Probability of Exceeding a Target Level of Recovery in Resilience Analysis
Authors: Nocera, F., P. Gardoni, and G. P. Cimellaro. (2019)
Journal: ASCE Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
The resilience of a system is generally defined in terms of its ability to withstand external perturbations, adapt, and rapidly recover. This paper introduces a probabilistic formulation to predict the recovery process of a system given past recovery data and to estimate the probability of reaching or exceeding a target value of functionality at any time. A Bayesian inference is used to capture the changes over time of model parameters as recovery data become available during the work progress. The proposed formulation is general and can be applied to continuous recovery processes such as those of economic or natural systems, as well as to discrete recovery processes typical of engineering systems. As an illustration of the proposed formulation, two examples are provided. The paper models the recovery of a reinforced concrete bridge following seismic damage, as well as the population relocation after the occurrence of a seismic event when no data on the duration of the recovery are available a priori.
Keywords: Decision support, Recovery, Resilience, Resilience metrics, Probability, Reliability analysis
Title: Probabilistic seismic and tsunami damage analysis (PSTDA) of the Cascadia Subduction Zone applied to Seaside, Oregon
Authors: Park, H., M.S. Alam, D.T. Cox, A.R. Barbosa, and J.W. van de Lindt. (2019)
Journal: International Journal of Disaster Risk Reduction
This study presents a probabilistic seismic and tsunami damage analysis (PSTDA) due to both earthquake shaking and tsunami inundation from tsunamigenic earthquake events at a coastal community. In particular, this study evaluates the annual exceedance probability (AEP) of seismic and tsunami hazards through earthquake and tsunami modeling that share the same fault sources. Then, estimates of earthquake and tsunami impact on the built environment utilizing fragility functions is predicted spatially. The PSTDA evaluates the combined impacts of earthquake and tsunami through a stochastic approach that accounts for the accumulated damage due to seismic shaking and subsequent tsunami inundation. A case study is setup and applied to Seaside, Oregon, for tsunamigenic earthquake events originating from the Cascadia Subduction Zone (CSZ) in order to illustrate the application of the PSTDA evaluation framework. The PSTDA integrates as a step within a resilience-focused risk-informed decision making process, which includes the assessment of direct and indirect socio-economic losses due to tsunamigenic earthquake events.
Keywords: Earthquake damage, Multi-hazard, Probabilistic seismic and tsunami damage analysis (PSTDA), Tsunamigenic, Tsunami damage
Title: Effects of advection on predicting construction debris for vulnerability assessment under multi-hazard earthquake and tsunami
Authors: Park, H., and D.T. Cox. (2019)
Journal: Coastal Engineering
Post survey results from devastating events such as the 2010 Chile and 2011 Tohoku earthquake and tsunami reported that different types of debris could be generated and shifted landward during tsunami inundation. That advected debris can result in significant damage to structures and negative impacts on community resilience during the recovery process. To improve mitigation plans, minimize losses, and to improve the community resilience to future tsunami events, it is necessary to quantify the debris and predict its final distribution. In this study, we present a framework to quantify the amount and location of construction debris generated and advected from a multi-hazard earthquake and tsunami event. The framework performs fragility analysis based on maximum intensity measures of the hazards, quantifies the amount of debris, and then advects the buoyant portion of debris using a time-dependent inundation model to estimate the trajectory and final distribution of debris. We apply this framework to Seaside, Oregon, subjects to events from the Cascadia Subduction Zone for eight recurrence intervals over the range of 100 to 10,000 years. Comparison of the debris distribution with and without the advection model highlights the importance of including advection to understand the final debris distribution. We show that the final debris distribution could have a significant impact on the initial accessibility and functionality of critical facilities which would be difficult to estimate considering the hazard intensity only. We show how the volume of debris generated and advected increases with the decreasing annual exceedance probability (increasing return period) and how the location of the peak cross-shore debris profile is related to the maximum limit of tsunami runup. This analysis considers only buoyant construction debris and could be extended to consider nonbuoyant, natural (e.g., vegetation) and anthropogenic (e.g., vehicles, shipping containers, marine vessels) debris.
Keywords: Tsunami, Earthquake, Debris, Advection, Community resilience
Title: Integration of detailed household and housing unit characteristic data with critical infrastructure for post-hazard resilience modeling
Authors: Rosenheim, N., R. Guidotti, P. Gardoni and W.G. Peacock. (2019)
Journal: Sustainable and Resilient Infrastructure
This paper presents a methodology that generates and links high-resolution spatial data on households and housing units with heterogeneous characteristics (i.e., size, tenure status, occupied, and vacant) to residential buildings which in turn are linked to critical infrastructure. The methodology utilizes areal demographic data from the US Census, which are probabilistically linked to an inventory of housing units located in residential buildings. By allocating high-resolution household socio-demographic data to housing units in single and multi-family residential structures themselves linked to critical infrastructure systems, coupled engineering-social science modeling is possible. This paper presents a workflow for linking social science and engineering data to enable integrated models for community resilience. The methodology is applied to Seaside, Oregon, a coastal community with a year-round population of over 6,000 persons. The application highlights the benefits of integrating social science and engineering data. Benefits include facilitating coupled modeling, accounting for uncertainty, visualization, and spatial exploration of modeled results.
Keywords: Social systems, synthetic population, physical infrastructure, social vulnerability, community resilience
Title: Modified Goda Equations to Predict Pressure Distribution and Horizontal Forces for Design of Elevated Coastal Structures
Authors: Tomiczek, T., A. Wyman, H. Park, and D.T. Cox. (2019)
Journal: J. Waterway Port Coastal and Ocean Engr
A hydraulic physical model study was conducted to quantify horizontal forces and pressure distributions on an elevated structure under nonbreaking, impulsive breaking, and broken wave conditions. Regular wave trials with varying wave heights and periods were used to estimate phase-averaged horizontal pressure distributions at the time of the maximum horizontal force for a range of air-gap conditions, defined as the distance between the still-water level and the base of the elevated structure. Measured pressures for all wave conditions were compared to the Goda equations, originally developed for wave pressures on a vertical caisson breakwater and modified for elevated structures. For breaking waves, the pressure distribution predicted by both the modified Goda equations and equations in ASCE 7-16 were compared to measured pressures. The modified Goda equations showed good agreement with measured pressures and the total horizontal force per unit width and were generally conservative for all wave conditions over a range of structural elevations, including cases in which the structure was elevated above the still-water level. The ASCE 7-16 equations for breaking wave–induced pressures and forces were conservative by factors of 3–20. Results suggest that the modified Goda equations may be used to improve design guidance for at-grade and elevated coastal structures under wave loads with constant storm surge.
Keywords: Horizontal wave pressure distribution and force, Goda equations, ASCE 7-16, Elevated structures, Physical model
Title: Hidden Costs of Blight and Arson in Detroit: Evidence From a Natural Experiment in Devil's Night
Authors: Zahran, S., T. Iverson, S. McElmurry, S. Weiler, and R. Levitt. (2019)
Journal: Ecological Economics
About one-fifth of the total housing stock in Detroit, Michigan is vacant, blighted or abandoned. Abandoned homes are particularly vulnerable to arson, with an estimated 20 such structures set ablaze each day. In 2011 the Fire Commissioner of Detroit announced a policy of fire non-suppression for abandoned structures. The policy is referred to as "Let it Burn." While such a policy has the merit of focusing scarce firefighting resources on situations in which people's lives are immediately at risk, we show that the policy exposes residents city-wide to various hazardous inorganic gases (CO, SO2, and NO2) released in uncontrolled fire events. By exploiting an annual tradition in Detroit called Devil's Night, we overcome a measurement problem involving the statistical attribution of changes in city-wide air quality due to fire emissions, and we conservatively estimate per burn pollutant externality costs from inorganic gas releases that include health damages in excess mortality and hospitalization for circulatory conditions in elderly populations. The estimated present value health burden for elderly residents of Detroit due to cardiovascular complications resulting from arson-related emissions of CO is greater than $300 million dollars. Since this is only a subset of the total social costs attributable to arson, the results suggest that a large scale blight reduction program might be socially efficient. Building on our empirical findings, we argue that the dilemma facing Detroit has the structure of a classic poverty trap. The corresponding insights may be relevant for other so-called rust belt cities grappling with the ecological economics of depopulation, housing abandonment, and arson.
Keywords: Arson, Blight, Poverty trap, Detroit, Inorganic gases, Health
Title: Enhancing resilience of interdependent traffic-electric power system
Authors: Zou, Q., and S. Chen (2019)
Journal: Reliability Engineering and System Safety
Characterizing the interdependencies among highly interconnected critical infrastructure systems with adequate details is critical in devising cost-effective resilience improvement strategies. This study presents a bi-level, stochastic, and simulation-based decision-making framework for prioritizing mitigation and repair resources to maximize the expected resilience improvement of an interdependent traffic-electric power system under budgetary constraints. The upper level seeks to find the optimal resource allocation plan to maximize the expected attainable functionality gain. The lower level characterizes the functionalities of the traffic and electric power systems considering three types of interdependencies based on network flow analysis methods. The dynamic traffic assignment algorithm, rather than the static traffic assignment algorithm, is used in order to capture more realistic traffic dynamics in the congested urban roadway networks. Uncertainties in disruptions, traffic demands, and costs of mitigation and repair actions are also considered in the problem formulation. The problem is solved by the binary particle swarm optimization algorithm initialized with the knapsack-based heuristic, and the priority indices of disrupted components for mitigation and repair are then established based on the solutions. The proposed decision model is demonstrated using a portion of the traffic-electric power system in Galveston, Texas.
Keywords: Resilience, Interdependencies, Transportation network, Electric power network, Resource allocation, Dynamic traffic assignment