Shaping the future of nuclear reactors with digital twins: Current developments and perspectives

Digital Twin(DT) technology offers a transformative pathway to mitigate the fundamental trade-off in nuclear energy between uncompromising safety and economic competitiveness. This review synthesizes the state of the field, revealing a critical insight: despite progress, implementations of nuclear DTs globally remain nascent, predominantly confined to low-to-mid maturity levels. This developmental lag stems from unique, sector-specific challenges: severe data scarcity due to extreme in-vessel conditions, an irreconcilable trade-off between high-fidelity multi-physics model accuracy and real-time computational demands, and the “black-box” nature of data-driven artificial intelligence conflicting with nuclear safety demand for interpretability and verifiable trust. A comparative analysis against aerospace, power grid, maritime, and healthcare sectors confirms that nuclear applications face exceptionally stringent regulatory requirements and uniquely high technical barriers. To overcome these hurdles, this work establishes a comprehensive DT application framework and introduces a novel five-tier maturity hierarchy for nuclear reactors. This model provides a standardized, actionable roadmap for technological evolution—from basic simulation guidance to fully symbiotic autonomy—thereby positioning the DT as the indispensable engine for the future of safe, efficient, and intelligent nuclear power.