CRISP Type 2/Collaborative Research
- Principal Investigator: Satish Ukkusuri, Purdue University
- Co-Principal Investigator: Seungyoon Lee, Purdue University
- Co-Principal Investigator: Shreyas Sundaram, Purdue University
- Co-Principal Investigator: Laura Siebeneck, University of North Texas
- Sponsor: NSF - National Science Foundation
- Duration: 01/2017-12/2020
Understanding the recovery of communities after disruptions has important implications for efficiently allocating resources, better planning for disasters, and reducing time and cost of recovery. Virtually all communities are embedded in highly interdependent social and physical infrastructure. This coupling between social and physical networks can lead to complex cascading effects that cannot be understood by looking at these networks in isolation. The full implications of these interdependencies for the resilience of communities and their ability to recover after disasters are not currently understood. This research seeks an understanding of the underlying factors that lead to resilience and recovery of interdependent social and physical networks after disasters. The researchers will collect data from communities impacted by Hurricane Sandy to create and test modeling approaches for improved knowledge of both social and physical factors that lead to recovery. It will also lead to a better understanding of the interdependencies between the social and physical systems, and will identify potential tipping points where small changes in the social and physical systems significantly impact the recovery of the overall system. The findings from the study will allow governmental and emergency agencies to take actions that will accelerate system recovery and enhance its resilience. Students and underrepresented groups working on this project will gain exposure and experience working with a multi-disciplinary research team, thereby preparing them for tackling complex, systems-related challenges in their future careers. A workshop will be organized to disseminate the findings to the scientific community and various stakeholders who are involved in recovery processes.
The modeling of resilience in interdependent social and physical networks will be conducted using an interdisciplinary approach. First, the researchers will collect data pertaining to complex interdependencies that influence post-disaster recovery and decision-making. Second, the project will leverage insights gleaned from the data to identify utility functions that influence the decision-making of households, and formulate mathematical techniques based on game theory and network science for modeling and analyzing the tipping points that lead to recovery across social and physical networks. Third, the research effort will create novel state-estimation techniques using publicly available citizen data and develop multi-agent simulation models that will provide new decision-support tools for governmental agencies and emergency response organizations to model, test and predict the effects of recovery actions. The research will identify the role of network structure and function in the movement of the overall system towards better recovery states, and characterize the different events that transpire during community re-entry and recovery processes.
