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Development of Digital Twin-Informed Predictive Maintenance for Critical Components in Advanced Reactors

Research output: Contribution to journal › Conference article › peer-review

Abstract

Small modular reactors (SMRs) and microreactors, along with other advanced reactor (AR) technologies, are key to the future of nuclear energy. For these systems to achieve low operating costs, high reliability, and flexibility across applications, their operation and maintenance must be optimized. Digital twin (DT) technology is one of the technologies that enables real-time (or faster than real-time) monitoring and prognosis of critical components which are vital for operational efficiency, low costs, and enhanced safety of ARs, accelerating their deployment. DT technology provides dynamic virtual representation of physical assets by integrating real-time data, physics-based models, and advanced analytics, which is critical to optimizing the performance of the entire energy system throughout the life cycle. DTs empower engineers and operators to virtually explore different scenarios, configurations, and control strategies, allowing for the identification of optimal solutions that maximize reactor efficiency, safety, and economics.
Original languageEnglish
Pages (from-to)137-140
Number of pages4
JournalTransactions of the American Nuclear Society
Volume134
Early online dateJun 1 2026
DOIs
StatePublished - Jun 1 2026
EventANS Annual Conference, 2026 - Denver, United States
Duration: May 31 2026 → Jun 3 2026

INL Publication Number

  • INL/CON-26-89894
  • 211876

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