TERMS SPM: Scalable Predictive Analytics for Nuclear Plant Assets

TERMS SPM aims to develop scalable technologies for risk-informed predictive analytics to reduce overall maintenance costs and achieve condition-based monitoring and maintenance strategies. The study utilizes data related to a particular plant asset from a specific nuclear plant site to develop technologies to scale risk-informed predictive analytic algorithms across different plant assets at the plant site and across the nuclear fleet. The developed algorithms and codes are used to optimize maintenance strategy and estimate/forecast generation costs based on the state of health of the plant asset. The codes are custom-built for the nuclear industry using nuclear plant data, institutional knowledge, and plant-specific details, providing an unfair advantage over commercial software packages that can perform predictive analytics. The potential customers are the current fleet of light water reactors, modular reactors, and non-nuclear industries.

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