Autonomous anomaly detection of proliferation in the AGN-201 nuclear reactor digital twin

The expansion of global nuclear power necessitates advanced methods for analyzing proliferation indicators. This study introduces a novel application of the Isolation Forest Machine Learning (IFML) algorithm within a digital twin (DT) of the AGN-201 nuclear reactor to autonomously detect anomalies....

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Veröffentlicht in:	Annals of nuclear energy 2025-02, Vol.211 (C), p.110990, Article 110990
Hauptverfasser:	Treviño, Eduardo, Shields, Ashley, Stewart, Ryan, Darrington, John, Scott, Jonathan, Pope, Chad, Ritter, Christopher
Format:	Artikel
Sprache:	eng
Schlagworte:	Anomaly detection Autonomous Digital twin Isolation forest Machine learning Nuclear safeguards
Online-Zugang:	Volltext
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