How Spatial and Functional Dependencies between Operations and Infrastructure Leads to Resilient Recovery

Abstract

A fast recovery of infrastructure functioning is important to the well-being of residents and the economy following interruption or disaster. Assessing the chances of recovery, or creating plans to enable it, is difficult due to the many interactions between components and operations. From a modeling perspective, addressing this challenging problem requires a capability for constructing representations of the dynamic interactions between elements that addresses how hazard and failure effects cascade and how recovery efforts propagate. Here, a geospatial resilience assessment platform is proposed containing a modeling approach comprising the capabilities necessary to address the challenge of urban infrastructure and operation recovery assessment and planning. It is designed to be reusable and integrate with reusable damage assessment tools such as Hazus. The approach combines a novel means to construct geospatial dependency models that can assess element-by-element recovery over time through integration with a computational recovery assessment engine called the graph model for operational resilience. A sample model and assessment that illustrates recovery time assessment of infrastructure services to the buildings of a neighborhood subject to varying infrastructure failures are provided. The case provides indications of the degree of burden on emergency management sustainment resources that may exist and how risk treatments can improve recovery times. In particular, the impact of the order of component recovery is examined in a multi-infrastructure setting.