Dynamic Strain Capacity Analysis and Planning for Critical Infrastructure to Improve Community Resilience to Disasters

Juyeong Choi, Purdue University


Community resilience to natural disasters depends to a large extent on the adequacy of infrastructure services provided through seven interrelated layers of infrastructure systems: civil, civic, social, financial, educational, environmental and cyber/communication infrastructure layers. During a disaster, critical infrastructure systems often fail to accommodate stress due to the combined effects of spikes in demand, compromised capacity, and cascading failures, thereby intensifying the impact of the disaster. Therefore, a community should have sufficient strain capacity for all seven layers of infrastructure to withstand post-disaster stresses and thus adequately serve a community’s recovery needs. For example, having sufficient capacity and an effective response plan to support the coordinated functioning of a multidimensional system is clearly vital when considering health-care issues in a disaster response situation. The compromised serviceability of the health-care system due to breaks in its cyber-physical-social network may pose a threat to public health during the response and relief phases. To ensure community resilience, it is important to quantitatively understand capacity needs across the seven layers of infrastructure during post-disaster recovery and systematically address them through proper pre- and post-disaster capacity building strategies. However, post-disaster resilience planning remains a challenge due to the nature of natural disasters as high-impact, low-probability events; a huge investment for disaster mitigation is often required in order to achieve the desired level of resilience. Therefore, there is a need for a decision support system (DSS) to facilitate pre- and post-disaster capacity building planning for resilient infrastructure within budget constraints. This research develops a framework for a DSS that helps a decision maker create an optimally balanced capacity building plan for both the pre- and post-disaster stages to address the ex post additional strain requirements of critical infrastructure during post-disaster recovery. To build the framework, this study proposes the use of the seven-layer classification (Deshmukh 2015) to model diverse patterns of interdependencies between different domains of infrastructure systems that are critical to understanding how a post-disaster community/infrastructure system functions. Furthermore, this research develops a methodology that collectively evaluates strain capacity needs across the seven layers of infrastructure with respect to the post-disaster stresses of an infrastructure system of systems. The stress–strain approach allows complex, heterogeneous infrastructure systems to communicate and prioritize their capacity needs for planning purposes within the seven-layer framework. To address system components that are vulnerable to excessive stress, this study pursues a balanced capacity building plan for the pre- and post-disaster stages, thereby achieving the desired level of resilience within budget constraints for mitigation planning. The decision maker interacts with the DSS to change the budget constraints as needed to find not only a feasible level of resilience but also desirable one. In terms of methodology, this research aims to understand the interdependencies between the seven interrelated layers of infrastructure and address the capacity needs for these interdependencies to achieve the desired level of community/infrastructure resilience. To this end, this study uses the stress–strain principle that is well known in structural engineering, specifically within the context of civil infrastructure. This research expands the principle to analyze the strain capacity needs of the seven layers of infrastructure because the stress and strain of such multidimensional systems must be quantitatively measured and analyzed to support capacity building planning. Overall, this research establishes a theoretical underpinning to quantify the post-disaster operations of an infrastructure system of systems based on various post-disaster case studies and the existing body of literature. As a proof of concept, we investigate the operations of the Iowa health-care system and its associated layers of infrastructure during the 2008 Midwest floods to (i) understand the relationship between stress and strain in the context of a health-care system of systems and (ii) demonstrate how this understanding can help in the creation of a pre- and post-disaster capacity building plan through the proposed DSS.




Hastak, Purdue University.

Subject Area

Engineering|Civil engineering

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