EAGER: Adaptive Digital Twinning: An Immersive Visualization Framework for Structural Cyber-Physical Systems

Infrastructure systems in the United States include a diverse series of assets, systems, and networks that are vital to the nation’s economy, security, and integrity. Members of every community, ranging from individual families to global corporations, rely on these infrastructure systems to thrive and maintain a high quality of life. This infrastructure is complex, interdependent, interconnected, and diverse, encompassing the water that we drink, the power that we use, the transportation services that move us, and the communication systems that connect us.

Many of these infrastructure systems that serve society today were built during the second industrial age, and in many cases are in a state of disrepair with decreasing resources to preserve them. While we have continued to improve design approaches and implement more sustainable preservation strategies, modern infrastructure systems still follow many of the historical approaches used in their early development and have not been modernized.

As societal dependence on technology continues to grow, the underlying physical infrastructure systems must be preserved, but also modernized to ensure that these systems are equipped to serve as the smart and agile cyber-physical systems (CPS) the future demands. This project will explore a high-risk/high reward approach to modernizing infrastructure systems using artificial intelligence-informed digital twins.

The digital twinning of an infrastructure system will form a collaborative feedback loop between the measurable data of the physical world and simulated processes in the virtual world, providing a domain-specific adaptation of the broader CPS framework necessary to inform decision-making.

Applied to the domain of large-scale structural systems, this project will test the hypothesis that immersive engagement using a digital twin representation of these structural systems will enable participants to observe, interact, and contextualize the complex behavior mechanisms associated with these systems in their operational environment. To test the hypothesis, the research design will explore a series of technology innovations including the formulation of artificial intelligence models to emulate both simulation-based results and experiment-based measurements.

Leveraging these technology innovations, we will be able to 1) understand to what extent can artificial intelligence formulated models effectively emulate the complex mechanical behaviors of simulation and experimentation of large-scale structural system; 2) evaluate to what extent does the development of artificial intelligence formulated models enable the real-time, bi-directional interaction between simulation and experimentation required of a digital twin; and 3) characterize how the deployment of artificial intelligence formulated models within an immersive environment allow end users to observe and characterize operational states of an in-service structural system. Success of this work will be realized through the fusion of experimental and numerical descriptions of these complex cyber physical systems and the creation of novel processes necessary to overcome the knowledge gap that exists between the theoretical descriptions of behavior and real-life structural response, forming a foundation for real-time decision-making for structural systems in their operational environments.

Results from this project will be disseminated to the broader research community through refereed journals, conference proceedings, and student dissertations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.