Abstract
This paper presents the results of an ongoing research and development effort to develop an online monitoring (OLM) system to support autonomous microreactor operations. A key component of this work is an evaluation of artificial intelligence (AI) and machine learning (ML) techniques to identify, diagnose, and predict problems with sensors and processes of the reactor. As described herein, selected methods of AI/ML were used to identify and diagnose anomalous sensor and system behaviors using data from a thermal-hydraulic flow loop and from operating nuclear power plants. This work serves to further the state of the art in OLM technologies for nuclear reactor applications and will ultimately result in a comprehensive system to enable OLM of critical structures, systems, components, and processes in microreactors.
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