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Developing a quantitative, predictive theory of network resilience; Interdisciplinary Northeastern team awarded NSF grant

An interdisciplinary group of Northeastern professors and researchers have been awarded a National Science Foundation (NSF) grant to develop a quantitative, predictive theory of network resilience.

The team’s vision is to develop a framework that will guide city officials, utility operators, and public agencies in developing new strategies for infrastructure management and urban planning. “This research will be of interest to a variety of other fields, from ecology to cellular biology,” the proposal states.

The $2.5 million Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) award brings together Robert Gray Dodge Professor of Network Science Albert-Laszlo Barabasi, with co-PIs Kathryn Coronges, Executive Director of Northeastern’s Network Science Institute; Stephen Flynn, Founding Director of the Global Resilience Institute; Edmund Yeh, Professor of Electrical and Computer Engineering; Auroop Ganguly, Associate Professor of Civil & Environmental Engineering; Sean Cornelius, a Post-Doc at the Center for Complex Network Research; Robert Sampson, Henry Ford II Professor of the Social Sciences at Harvard University and founding director of the Boston Area Research Initiative; and Baruch Barzel, physicist, applied mathematician and professor at Bar-Ilan University.

“Recent events in Florida and Texas have underscored the vulnerability of coastal communities to extreme meteorological events and climate change,” said Cornelius. “We need a better understanding of the interdependencies between infrastructure systems…What we would like is to be able to quantify resilience with a relatively small number of measures.”

The team will begin collecting data in Boston before embarking on a large scale mapping project, to visualize Boston’s physical and social structures — and the interdependencies which emerge. The team will work to develop accurate characterizations of the systems, as well as models and simulations that can act on the data, so the numbers will be able to accurately forecast how vulnerable a system is to a hypothetical natural disaster.

“We actually do have the power to predict things with foresight, not hindsight,” said Cornelius.

Interdependent Network-based Quantification of Infrastructure Resilience (INQUIRE)

“Critical infrastructure systems are increasingly reliant on one another for their efficient operation. This research will develop a quantitative, predictive theory of network resilience that takes into account the interactions between built infrastructure networks, and the humans and neighborhoods that use them. This framework has the potential to guide city officials, utility operators, and public agencies in developing new strategies for infrastructure management and urban planning. More generally, these efforts will untangle the roles of network structure and network dynamics that enable interdependent systems to withstand, recover from, and adapt to perturbations. This research will be of interest to a variety of other fields, from ecology to cellular biology.

“The project will begin by cataloging three built infrastructures and known interdependencies (both physical and functional) into a “network of networks” representation suitable for modeling. A key part of this research lies in also quantifying the interplay between built infrastructure and social systems. As such, the models will incorporate community-level behavioral effects through urban “ecometrics” — survey-based empirical data that capture how citizens and neighborhoods utilize city services and respond during emergencies. This realistic accounting of infrastructure and its interdependencies will be complemented by realistic estimates of future hazards that it may face. The core of the research will use network-based analytical and computational approaches to identify reduced-dimensional representations of the (high-dimensional) dynamical state of interdependent infrastructure. Examining how these resilience metrics change under stress to networks at the component level (e.g. as induced by inundation following a hurricane) will allow identification of weak points in existing interdependent infrastructure. The converse scenario–in which deliberate alterations to a network might improve resilience or hasten recovery of already-failed systems–will also be explored.”

Abstract Source: NSF