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91��Ƭ��’s Yufei Tang, Ph.D., Receives Prestigious NSF CAREER Award

Yufei Tang, Ph.D., an assistant professor, Department of Electrical Engineering and Computer Science, and a fellow of 91��Ƭ��'s I-SENSE.

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91��Ƭ��’s Yufei Tang, Ph.D., has received the coveted National Science Foundation (NSF) Early CAREER award. The CAREER program offers the NSF’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.

Tang, an assistant professor in 91��Ƭ��’s Department of Electrical Engineering and Computer Science within the College of Engineering and Computer Science, and a fellow of 91��Ƭ��’s Institute for Sensing and Embedded Network Systems Engineering (I-SENSE), received a $634,514 NSF CAREER award grant.

His project titled, “Physics-Reinforced Data-Driven Prognostics and Co-Design for Marine Hydrokinetic Energy Systems,” will fundamentally advance knowledge related to monitoring and designing marine and hydrokinetic energy systems, including marine current turbines and wave energy converters.

“Marine and hydrokinetic systems could contribute significantly to a diversified energy economy, improving the nation’s energy security and reducing reliance on fossil fuels,” said Tang. “However, these systems generate power from powerful resources such as strong water currents and/or large waves, which impose physical stresses on the equipment that are several times greater than wind turbines of similar power ratings. These constraints lead to stringent design requirements that increase capital costs. Further, operation and maintenance costs are high because access to equipment is limited due to their offshore geographical location and harsh corrosive environments.”

This project will provide the theoretical and computational foundation to enhance marine and hydrokinetic systems’ maintainability, survivability and efficiency. Results from this research will establish a solid foundation for robust predictive monitoring and co-design of complex large-scale dynamic systems, such as onshore and floating offshore wind farms, connected vehicles, and intelligent structures.

The long-term goal is to transform the conventional marine and hydrokinetic systems’ turbine design process from a sequential approach, where subsystems are designed individually and strong coupling among them is neglected, generally leading to a suboptimal design, to a novel co-design framework that simultaneously accounts for control, reliability and operational expenditure of the overall marine and hydrokinetic system with coupled subsystems. This simultaneous co-design at the earliest stage allows for mutually beneficial subsystems and could significantly improve the overall system performance.

The project will address three research challenges: data scarcity to train an effective prognostics/ diagnostics model for marine and hydrokinetic systems since the industry is new; data quality and concept drift because system dynamics may change over time and sensor data are subject to failures since marine and hydrokinetic systems devices are deployed in harsh, remote areas for long-term operation; and heterogeneous, multi-directional couplings and co-optimization because turbine geometry, control, reliability and maintenance strategies should be designed simultaneously to optimize turbine performance.

Tang and the project team will build responsive surface models that represent the relationships between design parameters and performance index, based on both experimental data and dynamical simulations. White-box co-optimization tools based on deep neural decision trees, an AI technique, will be developed to optimize the turbine design parameters. He will be working closely with 91��Ƭ��’s Southeast National Marine Renewable Energy Center (), designated by the United States Department of Energy as one of four national renewal energy centers, and James H. VanZwieten Jr., Ph.D., associate research professor in 91��Ƭ��’s Department of Civil, Environmental and Geomatics Engineering.

“This important NSF CAREER award is a major milestone in professor Tang’s successful career and will help to improve energy systems and accelerate progress in the blue economy,” said Stella Batalama, Ph.D., dean, College of Engineering and Computer Science. “Results from this research will be disseminated in collaboration with the National Renewable Energy Lab and industry partners, as well as through open-source tools, accelerating technology transfer. Importantly, outcomes will be integrated into new research-intensive curricula and a new energy resiliency certificate and will provide opportunities for students from groups underrepresented in STEM to participate in marine renewable energy research.”

Tang’s research interests are in the areas of artificial intelligence and cyber-physical energy systems. His current research focus is on developing theory and algorithms of big data analytics, graph learning and physics-informed neural networks for addressing critical challenges in predictive health monitoring of critical equipment, control co-design of energy systems, smart grid cybersecurity and environment monitoring.

Tang also was an Early-Career Research Fellow of the National Academies Gulf Research Program. He received his Ph.D. in electrical engineering from the University of Rhode Island in 2016.

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