Papers
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Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems
10:00–10:25AM EDT
Xingang Zhao (ORNL), Bryan Maldonado Puente (ORNL), Siyan Liu (ORNL), Seung-Hwan Lim (ORNL), William Gurecky (ORNL), Dan Lu (ORNL), Matthew Howell (ORNL), Frank Liu (ORNL), Wesley Williams (ORNL), Pradeep Ramuhalli (ORNL)
Quantifying Uncertainty of Deep Reinforcement Learning Based Decision Making for Operations and Maintenance of Nuclear Power Plant
10:25–10:50AM EDT
Ryan M. Spangler (Univ. Pittsburgh), Daniel G. Cole (Univ. Pittsburgh)
Development of a Virtual Sensor for Leading Edge Flow Meter Measurements in Nuclear Power Plants
10:50–11:15AM EDT
Brent Shumaker (Analysis and Measurement Services Corp.), Christopher Guillotte (Analysis and Measurement Services Corp.), Brian Moazen (Analysis and Measurement Services Corp.), Zachary Becker (Analysis and Measurement Services Corp.), Jamie Coble (Univ. Tennessee, Knoxville)
Presented by Ryan O’Hagan (Analysis and Measurement Services Corp.)
Using Machine Learning to Extract and Normalize Historic Maintenance Data from Work Descriptions
11:15–11:40AM EDT
Nicholas Zwiryk (Westinghouse Electric Co.), Steven Yurkovich (Westinghouse Electric Co.)
Discussion
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