ANALYZING WASTE PIT CONTAMINANTS

from CMU Civil & Environmental Engineering - Fall 2022

UNDERSTANDING ACTIVE MATTER UNLOCKS NEW MATERIAL PROPERTIES

as a case study. In that work, he is using data and algorithms to infer how people determine the need to travel, the destination, transportation mode, parking, and departure time. “We want to know not just how but why they’re using infrastructure,” says Qian. With this knowledge, cities could make changes that improve mobility, safety, emissions, and more.

Additionally, the model includes things like event traffic, accidents, and extreme weather to provide information for response and resource allocation plans. “Say we set the digital twin so that an incident on the highway closes two lanes at 4 pm. We may assume a fraction of people learn about it from their smartphones and others have no idea what's going on,” says Qian. “The simulation can show what happens if we focus on dispatching response teams faster. Maybe we invest in rerouting people and disseminating accurate, timely information. We might tune nearby signal timing. Once we know how people respond in these situations, these levels can all be examined in the digital twin.”

lines. To do so, he is using factory field notes, videos, and control system logs. The finished digital twin platform will generate data-driven suggestions for improving human-machine efficiency, safety, and health as well as adjusting workspaces for new components and designs.

Analyzing human behavior and decision-making in operations is a theme across much of Tang’s work. For example, working with the Federal Aviation Administration and NASA’s Ames Research Center, he created a digital twin of the Los Angeles airport air traffic. That simulation is allowing researchers to study how air traffic controllers make decisions as well as how AI learning from data-driven airport operation simulations could help prevent future mistakes. Elsewhere, Tang is modeling the actions of nuclear power plant workers with Arizona Public Services in the hopes of identifying what activities are essential during plant outages. Eventually, AI could learn from nuclear plants’ communication and operation histories and alert workers to take appropriate actions in similar contexts. “My work is complementing machine learning with human learning. Can a machine observe and

learn when and why experienced human operators perform better than automatic control systems?” says Tang. “To model how intelligence systems should help humans in these complex situations, we need algorithms for capturing and analyzing human behavior together with machine behavior.” Faculty member Sean Qian's research on "improving urban mobility, emissions, and Sean Qian infrastructure systems working," involves large-scale dynamic network modeling and data analytics for transportation systems. In a recent collaboration with Honda USA, he replicated the flow of individual, ridesharing, and public transit vehicles through Columbus, Ohio. Now, he is using that digital twin to analyze the impact of increased electric vehicle usage on power grids and mobility systems as well as develop strategies to mitigate loads to both systems.

Corey Harper Qian is also modeling how people and traffic move through cities for a project with the technology company Fujitsu, using the Washington DC metro area

FINDING SUSTAINABLE AND EQUITABLE FOOD DELIVERY MODELS

Another faculty member modeling city systems is Corey Harper, working with CEE faculty Greg Lowry, Destenie Nock, and Costa Samaras, along with faculty from two other departments.

Their partners include the Puget Sound Regional Council, grocery chain Giant Eagle, and driverless vehicle solution provider Easy Mile. Together, the team is using digital twins as a virtual testbed for simulating environmental, equity,

Greg Lowry Destenie Nock Costa Samaras

and traffic impacts of food delivery systems that use trucks, sidewalk robots, and aerial drones. For example, they are using a Seattle traffic model to examine how different delivery strategies, adoption levels, and shopping patterns would change regional emissions and traffic. The team also created a tool for modeling individual intersections when a more microscopic focus is needed.

“From the equity side, we’re looking at things like which areas and populations would experience congestion and emissions increases,” Harper explains. “How do different demographic groups and people with different incomes feel about food delivery?”

Creating Glacial Models to Inform Climate Action

Recent and anticipated future changes in the earth’s glaciers have major implications for sea level rise, flooding, and the availability of water resources. CEE faculty member David Rounce and his research team are working to refine models that demonstrate and predict the response of glaciers, water resources, and hazards due to a changing climate. Their computational models incorporate data from field visits, satellite images, and remote sensing. In fact, Rounce and PhD student Albin Wells recently returned from Alaska, where they deployed and retrieved time-lapse cameras built in collaboration with faculty member Katherine Flanigan and PhD student Cheyu Lin.

Once complete, the group’s work could shape policies for safe, sustainable, and equitable delivery. Companies could also use the tools to test how different delivery models would affect cost, food access, energy use, emissions, and profitability within neighborhoods.

BRINGING TOGETHER EXPERTISE AND INDUSTRIES

For Harper, having an interdisciplinary team has been essential to building a robust digital twin that considers everything from equity to delivery optimization. “It would be hard for any one of us to do this alone,” he says. “The collaboration makes for a digital twin that can answer really interesting questions.” He is far from the only faculty member Rounce’s team is currently partnering with NASA on two projects, including one to improve projections of how glaciers will contribute to sea-level rise through 2100. Ultimately, Rounce hopes their work will help to support more proactive decision-making and policies for local, regional, and global climate adaptations and mitigation.

who values a collaborative, big-picture approach. “A lot of people are thinking about digital twins for very specific purposes, but ultimately we need to integrate all those things together,” says Mario Bergés. “A digital twin that only answers one specific question will not get us very far.”

Electric autonomous vehicles that deliver goods from stores to customers' homes. (Image: Nuro) Already, Sean Qian has been working to bring together crossindustry partners for sharing research progress and data and producing digital twins that match our interconnected world. Autonomous vehicles and smart buildings, he points out, rely on wireless networks. Electric vehicle use impacts the power grid. Large events not only slow traffic, but also strain cellular towers.

“To enlarge our broader impact, we need partners across the ecosystem. By bringing sectors together, we can build better digital twins of mobility, energy, power, internet of things, wireless communication, everything,” says Qian. “CEE’s expertise in computing and infrastructure places us in a central role for connecting all of these domains.”