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Predicting How Climate Change Affects Infrastructure

Engineers create a digital twin to understand the effects of climate change on critical infrastructure

by University of Pittsburgh
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A digital twin may sound like something out of a science fiction film, but Pitt engineers are developing new technology to make them a reality in our campus and beyond.

Digital twins—a model that serves as a real-time computational counterpart—can be used to help simulate the effects of multiple types of conditions, such as weather, traffic, and even climate change. Still, life-cycle assessments (LCAs) of climate change’s effects on infrastructure are still a work-in-progress, leaving a need for a comprehensive view on how this can impact a building’s daily function. 

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A team from the University of Pittsburgh Swanson School of Engineering received $735,872 from the National Science Foundation to develop a digital twin of the Mascaro Center for Sustainable Innovation (MCSI), a university-wide sustainability center attached to Pitt’s engineering school in Benedum Hall, to help forecast and mitigate future climate change consequences on infrastructure. 

“Understanding this complex relationship between environmental demand and performance of vertical infrastructure will help us develop response strategies and unlock advanced climate adaptation with the ultimate goal of minimizing energy consumption and greenhouse gas emissions,” said assistant professor Alessandro Fascetti, who will be the lead principal investigator on the project.

A real-time look into understanding and slowing climate change

Though we live in an increasingly industrialized, urban world, construction of both horizontal and vertical infrastructure is one of the major sources of greenhouse gas emissions (GHG). 

By developing a digital twin, Fascetti, along with Melissa Bilec, co-principal investigator, William Kepler Whiteford Professor, and director of MCSI; and John Brigham, associate professor of civil and environmental engineering, can develop, implement and validate a framework for real-time monitoring of and predictions for the MCSI building. 

The MCSI building, a LEED gold-certified facility constructed in 2007 and a product of a former NSF award received by Bilec, is equipped with an advanced energy consumption and indoor air quality sensing system. In addition to building automation systems and metering common to other Pitt structures, detailed electrical consumption is sensed with multiple panel-based electrical meters and Heating, Ventilation, Air Conditions (HVAC) system flowmeters, while Indoor Environment Quality (IEQ) data is collected using the AirCuity OptiNet System, an indoor air quality sensing system that features a central sensor suite and unique structured cables housing air sampling tubes and control wires. 

The research team will leverage extensive background in dynamic LCAs, material flow analysis, reality capture, adaptive building envelopes, mechanic-based design optimization, artificial intelligence, and mechanistic machine learning to develop a new holistic frame for the assessment and prediction of the performance of vertical infrastructure throughout their life cycle. 

“Because of the diverse streams of data we can obtain in real-time from the MCSI, we’ll be able to focus on developing a novel digital twin framework for the quantification of GHG emissions associated with the operation of vertical infrastructure to minimize its environmental footprint by designing and deploying environmentally responsive building envelopes,” Fascetti said.

- This press release was originally published on the University of Pittsburgh website