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DOE OSTI · 3030863

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

Godbole, Chaitee Milind [Idaho National Laboratory]·Yadav, Vaibhav [Idaho National Laboratory] (ORCID:0000000244504345)·Chen, Edward [Idaho National Laboratory] (ORCID:0000000180088097)·Alam, Syed Bahauddin [UIUC]·Agarwal, Vivek [Idaho National Laboratory] (ORCID:0000000313340509)
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Abstract

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

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Godbole, Chaitee Milind [Idaho National Laboratory], Yadav, Vaibhav [Idaho National Laboratory] (ORCID:0000000244504345), Chen, Edward [Idaho National Laboratory] (ORCID:0000000180088097), Alam, Syed Bahauddin [UIUC], Agarwal, Vivek [Idaho National Laboratory] (ORCID:0000000313340509). 2025-06-18. Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques. https://www.osti.gov/biblio/3030863

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