New tool to guide recovery from disasters

New York: Indian-origin researchers have developed a computerized tool for guiding stake-holders in the recovery of large-scale infrastructure systems in the aftermath of a disaster.

“The tool, based on a quantitative framework, identifies the order in which the stations need to be restored after full or partial destruction,” said Udit Bhatia, graduate student at Northeastern University in Boston.

Bhatia, under the direction of associate professor Auroop Ganguly, drew on network science to develop the tool.

“We found that, generally, the stations between two important stops were most critical,” he said, alluding to the network science concept of “centrality measures,” which identify stations that enable a large number of station-pairs to be connected to one another.

The tool can be used to restore transportation network, water-distribution systems, power grids, communication networks, and even natural ecological systems, the study said.

For the study, Bhatia mined open-source datasets on ticket-reservation websites to track the origins and destinations of trains running on the Indian rail network.

He then constructed a complex network, with the stations as nodes and the lines connecting those nodes as the ‘edges,’ or links, between them, and overlaid it on a geographical map of the country.

Next he applied natural and man-made disasters to the system, knocking out stations using network science-derived algorithms.

“We considered real-life events that have brought down this network,” said Bhatia, ticking off the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout due to a power grid failure, as well as a simulated cyber-physical attack, partially modelled after the November 2008 Mumbai terror attack.

This unique tool, which has been filed for invention protection through Northeastern University’s center for research innovation, also informs development of preventative measures for limiting damage in the face of a disaster, according to the researchers.

The study appeared in th journal PLOS ONE.