Community Building Portfolios
(Portfolio-level Damage, Functionality Loss and Recovery)
We developed a framework for resilience-based building inventory analysis under earthquake hazard, including formulations for: (a) probabilistic building inventory damage and direct loss estimation, considering the positive correlations in seismic demands due to common hazard with large footprint and in building capacities due to common design, construction practice and code enforcement [Lin & Wang, 2016]; (b) probabilistic spatial distribution of post-earthquake building portfolio functionality loss considering utility disruptions, by coupling a state-of-art minimum cost based network interdependency model with a comprehensive building inventory damage analysis procedure [Zhang et al, 2016]; (c) stochastic modeling of community building portfolio recovery by coupling the physical process of building-level repair and rebuilt with the community-level resource, preference, and social-economic characteristics [[Lin & Wang, 2017a, 2017b], (d) multi-objective decision algorithms to optimize pre-event building portfolio retrofit strategies that support overall community resilience objectives [Lin et al, 2016; Wang & Wang, 2017]; and (e) interface modeling between building inventory damage estimation and economic impact prediction using computable general equilibrium (CGE) model [Cutler, 2016] (through collaboration with the COE Economic Team), which leads to other on-going investigation of effective non-engineering risk mitigation solution for community building inventory resilience planning.
Related Links: COE Building Task Highlight
(Resilience-based Decision on Mitigation, Response and Recovery)
We have developed a decision framework for risk-based, stage-wise resilience planning of transportation networks, including pre-disaster (Stage I) mitigation prioritization, resource allocation during emergency response immediately following a hazard (Stage II), and post-event long-term (Stage III) recovery optimization. This framework includes (i) a stage-wise metric system of three network performance metrics that are uniquely formulated to support the specific decision process in each of the three planning stages, respectively [Zhang et al, 2017],; and (ii) a stage-wise decision model that is formulated as stochastic multi-objective optimization problems, including a Stage-I project ranking mechanism to select pre-disaster retrofit projects under budget constraints[Zhang & Wang, 2016], a Stage-II prioritization method to identify locations for temporary paths to facilitate post-disaster emergency rescue under time pressure, and a Stage-III scheduling approach for sequencing repair construction interventions for network’s long-term recovery [Zhang et. al, 2016]. This framework has been implemented to roadway network of Shelby County, TN, subjected to seismic hazards [Zhang et al, 2017].
Cascading Failure and Interactive Recovery of Community Physical Systems
(Coupling Resilience Modeling of Building Portfolios, Roadway Systems and Utility Networks)
We introduce a new probabilistic framework to predict the post-disaster functionality loss of community built environment including building portfolios, utility systems and transportation networks [Zhang, Lin, et al, 2017]. The framework fully couples the functionality analyses of physical systems of distinct topologies and hazard response characteristics on a consistent spatial scale at the community level, providing a physics-based, quantitative measure of functionality loss of built environment across the geographic domain of the community. Uncertainties and spatial correlations in both hazard demand and structural response parameters in each of the involved physical systems are propagated throughout the analysis framework. Cascading failures among interdependent networks are modeled using a state-of-the-art network flow-based, mixed integer linear programming model. This analysis reveals and quantifies the comprehensive spatial patterns of functionality loss of a community built environment, which are jointly determined by spatial variation of hazard intensity, inherent vulnerably of buildings and components of utility systems, cascading failures in interdependent utility networks, as well as the redistribution of surplus supply capacity in the utility networks, providing rich array of information for hazard mitigation. Ongoing research is to conduced to extend this coupled analysis to the recovery phase.
Flood Modeling at Community Scale
(Flood Modeling that Directly Support Community Resilience Planning)
Effective risk-based community resilience planning requires physics-based hazard-modeling technologies, which can provide time series of hazard demand parameters that directly support civil infrastructure damage and functionality loss assessment at community or regional scales. We have developed, hydrology models that can capture the temporal and spatial variation in demand parameters (water depth, flow velocity, inundation duration, etc.) as well as the correlations among these demands in precipitation-induced flooding events [Xue X. et al, 2017], through collaboration with National Weather Center located on the OU Research Campus. Such information is critical to characterize the correct spatial distribution of risk that is of paramount importance for natural hazard mitigation to civil infrastructure within communities [Dresback, K.M. et al, 2017].