Understanding Complex Infrastructure Systems
Duke team combines real-world data with computer simulations to analyze complex and changing infrastructure systems—from the biological to the geological
From prospecting for fossil fuels to implanting synthetic heart valves, human engineering is fast transforming natural environments. But how are our interventions affecting these systems—and vice-versa?
Duke engineers are tackling those questions in a new initiative using “heavy data” methodologies to analyze complex infrastructure systems that change over time and space, such as those in the biological or geological realms.
“We can use data analytics techniques to predict how these systems will behave, but the standard datasets are based on a relatively small number of observations and measurements,” said John Dolbow, professor in CEE. “We want to augment the collected data with model-based simulations of the physical mechanisms and processes involved in the system being studied.”
By incorporating both real-world data and computer simulations, the resulting “heavy data” offers more robust information, lending a greater degree of certainty to predictions.
“We believe this will be a powerful approach to help engineers understand, design and manage complex systems across a range of important areas, from climate mitigation to energy exploration,” said Guglielmo Scovazzi, associate professor of CEE (pictured above with students).
“This is really a new paradigm for engineering,” said CEE professor Wilkins Aquino. “Duke has considerable strengths in both data analytics and model-based simulation, and we anticipate this initiative will serve as a model for how methodologies from different fields can be integrated to solve big problems in new ways.”