Presented By: Nuclear Engineering & Radiological Sciences
NERS Colloquium: The Future is Now: the Intersection of Robotics, Cybersecurity, AI, and Advanced Nuclear
Speaker: Fan Zhang, Georgia Tech
Abstract:
As nuclear energy expands its capacity and operational scope to meet evolving energy needs and combat climate change, it is essential to reduce operation and maintenance costs to maintain economic viability. While robots have been used in the past for reducing costs through applications such as surveys, their potential in nuclear power plant operations has been under-explored thus far. In this seminar, I will discuss our research integrating machine learning and robotics to develop advanced online monitoring and diagnosis systems which improve operational efficiency and reactor economics. This approach allows for an increase in sensing scope, reduction in human labor, and decreased human exposure to hazardous conditions. By using robots as a new, versatile and mobile sensing platform, this research improves the overall accuracy and effectiveness in identifying and resolving issues within the plant. Additionally, I will highlight our research on nuclear cybersecurity, which addresses pressing challenges in enabling a digital future for the nuclear industry. Join us for an informative discussion on how advanced technology and research is shaping the future of nuclear energy.
Bio:
Dr. Fan Zhang is an Assistant Professor in Mechanical Engineering at the Georgia Institute of Technology. She directs the Intelligence for Advance Nuclear (iFAN) lab in developing research which uses machine learning and AI to optimize nuclear power plant operations and enhance cybersecurity. Dr. Zhang is a Georgia Tech College of Engineering Cybersecurity Fellow. She received her Ph.D. in Nuclear Engineering and a M.S. degree in Statistics from the University of Tennessee, Knoxville in 2019. She is the recipient of the 2021 Ted Quinn Early Career Award from the American Nuclear Society for her contributions in the fields of instrumentation & control and cybersecurity. In 2022, she was awarded the inaugural Distinguished Early Career Award from the U.S. DOE Office of Nuclear Energy for her project “Robot-assisted Online Monitoring, Online Maintenance, and Dynamic Risk Assessment for LWRs and Advanced Reactors”. She has also been selected to the Class of 2023 Volunteer 40 Under 40 for her professional achievements and broad research impact.
As nuclear energy expands its capacity and operational scope to meet evolving energy needs and combat climate change, it is essential to reduce operation and maintenance costs to maintain economic viability. While robots have been used in the past for reducing costs through applications such as surveys, their potential in nuclear power plant operations has been under-explored thus far. In this seminar, I will discuss our research integrating machine learning and robotics to develop advanced online monitoring and diagnosis systems which improve operational efficiency and reactor economics. This approach allows for an increase in sensing scope, reduction in human labor, and decreased human exposure to hazardous conditions. By using robots as a new, versatile and mobile sensing platform, this research improves the overall accuracy and effectiveness in identifying and resolving issues within the plant. Additionally, I will highlight our research on nuclear cybersecurity, which addresses pressing challenges in enabling a digital future for the nuclear industry. Join us for an informative discussion on how advanced technology and research is shaping the future of nuclear energy.
Bio:
Dr. Fan Zhang is an Assistant Professor in Mechanical Engineering at the Georgia Institute of Technology. She directs the Intelligence for Advance Nuclear (iFAN) lab in developing research which uses machine learning and AI to optimize nuclear power plant operations and enhance cybersecurity. Dr. Zhang is a Georgia Tech College of Engineering Cybersecurity Fellow. She received her Ph.D. in Nuclear Engineering and a M.S. degree in Statistics from the University of Tennessee, Knoxville in 2019. She is the recipient of the 2021 Ted Quinn Early Career Award from the American Nuclear Society for her contributions in the fields of instrumentation & control and cybersecurity. In 2022, she was awarded the inaugural Distinguished Early Career Award from the U.S. DOE Office of Nuclear Energy for her project “Robot-assisted Online Monitoring, Online Maintenance, and Dynamic Risk Assessment for LWRs and Advanced Reactors”. She has also been selected to the Class of 2023 Volunteer 40 Under 40 for her professional achievements and broad research impact.
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